Dissertations / Theses: 'Inventory routing problem'

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Maqueo, Rodrigo Rubio. "Dynamic-stochastic vehicle routing and inventory problem." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/10593.

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Solyali, Oguz. "An Integrated Inventory Control And Vehicle Routing Problem." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/2/12606445/index.pdf.

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In this study, we consider a logistics system, in which a single supplier delivers a product to multiple retailers over a finite time horizon. Supplier decides on the amount to order in each period and services retailers facing deterministic dynamic demand via a fleet of vehicles having limited capacity. Each retailer has specific minimum and maximum levels of inventory in an order-up-to level inventory policy setting. The problem is to simultaneously determine the quantity of product to order to the supplier, retailers to be visited, the quantity of product to be delivered to retailers and routes of vehicles in each period so as to minimize system-wide costs. We present a mathematical formulation for the problem, for which we develop several Lagrangian relaxation based solution procedures providing both upper and lower bounds to the problem. We implement these solution procedures on test instances and present the results. Computational study shows that our solution procedures generate good feasible solutions in reasonable time.

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Alisan, Onur. "The Multiple Retailer Inventory Routing Problem With Backorders." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609681/index.pdf.

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In this study we consider an inventory routing problem in which a supplier distributes a single product to multiple retailers in a finite planning horizon. Retailers should satisfy the deterministic and dynamic demands of end customers in the planning horizon, but the retailers can backorder the demands of end customers considering the supply chain costs. In each period the supplier decides the retailers to be visited, and the amount of products to be supplied to each retailer by a fleet of vehicles. The decision problems of the supplier are about when, to whom and how much to deliver products, and in which order to visit retailers while minimizing system-wide costs. We propose a mixed integer programming model and a Lagrangian relaxation based solution approach in which both upper and lower bounds are computed. We test our solution approach with test instances taken from the literature and provide our computational results.

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Ozlem, Pinar. "The Inventory Routing Problem With Deterministic Order-up-to Level Inventory Policies." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606444/index.pdf.

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This study is concerned with the inventory routing problem with deterministic, dynamic demand and order-up-to level inventory policy. The problem mainly arises in the supply chain management context. It incorporates simultaneous decision making on inventory management and vehicle routing with the purpose of gaining advantage from coordinated decisions. An integrated mathematical model that represents the features of the problem is presented. Due to the magnitude of the model, lagrangean relaxation solution procedures that identify upper bounds and lower bounds for the problem are developed. Satisfactory computational results are obtained with the solution procedures suggested on the test instances taken from the literature.

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Song, Jin-Hwa. "Inventory Routing Investigations." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5028.

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The elimination of distribution inefficiencies, occurring due to the timing of customers' orders is an important reason for companies to introduce vendor managed inventory programs. By managing their customers' inventories, suppliers may be able to reduce demand variability and therefore distribution costs. We develop technology to measure the effectiveness of distribution strategies. We develop a methodology that allows the computation of tight lower bounds on the total mileage required to satisfy customer demand over a period of time. As a result, companies will be able to gain insight into the effectiveness of their distribution strategy. This technology can also be used to suggest desirable delivery patterns and to analyze tactical and strategic decisions. Secondly, we study the inventory routing problem with continuous moves (IRP-CM). The typical inventory routing problem deals with the repeated distribution of a single product, from a single facility, with an unlimited supply, to a set of customers that can all be reached with out-and-back trips. Unfortunately, this is not always the reality. We introduce the IRP-CM to study two important real-life complexities: limited product availabilities at facilities and customers that cannot be served using out-and-back tours. We need to design delivery tours spanning several days, covering huge geographic areas, and involving product pickups at different facilities. We develop a heuristic and an optimization algorithm to construct distribution plans. The heuristic is an innovative randomized greedy algorithm, which includes linear programming based postprocessing technology. To solve the IRP-CM to optimality, we give a time-discretized integer programming model and develop a branch-and-cut algorithm. As instances of time-discretized models tend to be large we discuss several possibilities for reducing the problem size. We introduce a set of valid inequalities, called delivery cover inequalities, in order to tighten the bounds given by the LP relaxation of the time-discretized model. We also introduce branching schemes exploiting the underlying structure of the IRP-CM. An extensive computational study demonstrates the effectiveness of the optimization algorithm. Finally, we present an integrated approach using heuristics and optimization algorithms providing effective and efficient technology for solving inventory problems with continuous moves.

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Zerman, Erel. "Multi-item Inventory-routing Problem For An Fmcg Company." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608927/index.pdf.

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In this study, inventory&ndash
routing system of a company operating in Fast Moving Consumer Goods (FMCG) industry is analyzed. The company has decided to redesign distribution system by locating regional warehouses between production plants and customers. The warehouses in the system are all allowed to hold stock without any capacity restriction. The customers are replenished by the warehouse to which they have been assigned. Customer stocks are continuously monitored by the warehouse and deliveries are to be scheduled. In this multi&ndash
item, two-echelon inventory&ndash
distribution system, main problem is synchronizing inventory and distribution decisions. An integrated Mixed Integer Programming optimization model for inventory and distribution planning is proposed with the aim of optimally coordinating inventory management and vehicle routing. The model determines the replenishment periods of items and amount of delivery to each customer
and constructs the delivery routes with the objective of cost minimization. The integrated model is coded in GAMS and solved by CPLEX. The integrated inventory-routing model is simulated with retrospective data of the company. Computational results on test problems are provided to show the effectiveness of the model developed in terms of the performance measures defined. Moreover, the feasible solution obtained for a period is compared to the realized inventory levels and distribution schedules. Computational results seem to indicate a substantial advantage of the integrated inventory-routing system over the existing distribution system.

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TAVARES, DIEGO MOAH LOBATO. "EXACT AND HEURISTIC APPROACHES FOR INVENTORY ROUTING PROBLEM VARIANTS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2018. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35787@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Esta pesquisa trata de duas variantes do conhecido Problema de Roteirização de Veículos com Estoque (do inglês Inventory Routing Problem – IRP). O problema nasce num contexto de um sistema de Vendor Managed Inventory (VMI) no qual o fornecedor é responsável pela gestão de estoques do cliente. Tal problema é a junção dos problemas de transporte e gestão de estoques, que correspondem aos maiores custos em uma operação logística. Destarte este trabalho apresenta um modelo matemático para uma variante do IRP que considera que o fornecedor tem clientes dentro e fora do sistema de VMI. Este caso surge quando para alguns clientes não é interessante a realização do controle de seus estoques dentro do sistema de VMI, somente o atendimento de suas demandas. Além disto, o modelo contempla três diferentes tipos de políticas de gestão de estoques e é capaz de lidar com casos contendo vários períodos e vários veículos. Após sua elaboração, o modelo foi validado em instâncias do IRP, do Problema de Roteamento de Veículos (do inglês Capacitated Vehicle Routing Problem - CVRP) e instâncias próprias para a variante. Foram realizados também estudos sobre os impactos das diferentes políticas de gestão de estoques. Além do modelo matemático, foi desenvolvida uma meta-heurística híbrida que resolve uma variante do IRP considerando vários períodos e vários veículos. Cada movimento considerado durante a meta-heurística é divido em duas etapas, a primeira sendo a modificação da posição de um ou mais clientes nos veículos e períodos e uma segunda etapa que resolve de forma exata um Problema de Fluxo Máximo a Custo Mínimo para a atribuição ótima do volume de carga transportada para cada cliente por cada veículo em cada período. Esta abordagem é então testada em instâncias clássicas para esta variante do IRP, obtendo resultados que comprovam a eficiência do algoritmo.
This research deals with two variants of the Inventory Routing Problem (IRP). This problem comes from the context of a Vendor Managed Inventory (VMI) system in which the vendor is responsible for managing the customer s inventory. It is the combination of transportation and inventory management problems, which correspond to the higher costs in a logistics operation. Hence, this paper presents a mathematical model for an IRP variant, in which the vendor has customers inside and outside the VMI system. This situation is presented when it is not interesting to manage the inventories of some clients within the VMI system, resulting only in meeting their demands. In addition, the model considers three different types of stock management policies and it can comprehend multiple periods and multiple vehicles. After its modelling, the model was validated using IRP instaces, the Vehicle Routing Problem (CVRP) and specific instances for this variant. The impacts of different inventory management policies were also analyzed. In addition to the mathematical model, a hybrid meta-heuristic was developed, which solves an IRP variant considering several periods and several vehicles. Each iteration of the metaheuristic is divided into two stages: the first is modifying the position of one or more customers attended by the vehicles and periods, and a second step that solves a Maximum Flow at Minimum Cost problem, to optimally assign the load volumes transported to each customer in each vehicle in each period. Then, this approach is tested in classical instances for this IRP variant, obtaining results that prove the efficiency of the algorithm.

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Cabo, Nodar Marta. "Exact and approximate algorithms for the inventory routing problem." Thesis, University of Southampton, 2003. https://eprints.soton.ac.uk/50599/.

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In this thesis we develop exact and approximate algorithms for the inventory routing problem (IRP). The inventory routing problem is one of deciding an optimal delivery policy for a set of customers through a given planning period. Customers can hold inventory and do not need deliveries every day. Deliveries are carried out by a fleet of homogeneous vehicles that must be routed to travel a minimum distance while visiting all customers scheduled for that day. Decisions concern which customers to be visited and how much to deliver to each of them must be taken. A new formulation for the IRP is presented as a mixed integer programming model. This new approach allows split deliveries so customers can receive the inventory through more than one vehicle during the same day. It also seeks periodic solutions through a given planning period. Although throughout our research the planning period is fixed, all algorithms presented in this thesis can be applied to any length of the planning period. Special cases for this problem are also considered and optimal polynomial algorithms have been developed. We develop four constructive heuristics for the inventory routing problem. These heuristics are based on a schedule-first route-second approach. First, a decision is made on which customers to visit each day, and how much inventory they should receive on each delivery. Then, a vehicle routing problem is solved for each day to perform the deliveries to the customers. Several experiments are carried out to compare the performance of each heuristic. An iterated local search method is then applied to the best solution obtained with these heuristics. The local search is based on node interchange and aims to reduce the number of routes per day as well as the total distance travelled. Extensive computational tests are carried out to asses the effectiveness of this local search procedure.

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Rahimi, Mohammad. "Inventory routing problem under dynamic, uncertain and green considerations." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEI049/document.

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La gestion des stocks et la maîtrise de la distribution sont les deux activités importantes dans le management de la chaîne logistique. L’optimisation simultanée de ces deux activités est connue sous l’intitulé du problème de gestion de stock et de tournée de livraison (Inventory Routing Problem, IRP). L’IRP traditionnelle est confronté aux différents problèmes, causé principalement par le manque d'informations complètes et/ou temps réel, tels que les changements de la demande, l’embouteillage soudain causé par un accident, etc. Le partage et la mise à jour d'information logistique peut améliorer l'efficacité d’IRP. De plus, en raison de la spécificité de l'IRP dans la logistique urbaine, il est important de considérer d'autres critères comme les critères sociaux, environnementaux et le niveau de service qui pourraient être en conflictuel. L’objectif principal de cette thèse est de développer des modèles et des méthodes des IRP avec la prise en compte des incertitudes, du niveau de service et de l’impact environnemental, social en finalement les informations du temps réel (IRP dynamique). Dans cette thèse, trois modèles mathématiques sont proposés. Le premier modèle multi-objectif est pour identifier un compromis entre le niveau de service, les critères environnementaux et économiques. Pour gérer des paramètres incertains, on applique une approche floue. Dans le deuxième modèle, nous avons étudié l'impact des critères sociaux sur les IRPs en proposant un modèle mathématique bi-objectif. Une approche stochastique basée sur des scénarios est développée pour faire face à l'incertitude dans le modèle. Enfin, le troisième model concerne l'impact de l'utilisation d'informations du temps réel dans les IRP. Il est à noter que, selon la durée de vie du produit tant sur le plan financier que sur le plan écologique, les produits périssables sont considérés dans les trois modèles proposés. Les résultats montrent une gestion dynamique est beaucoup plus efficace que la statique
The inventory management and transportation are two main activities of supply chain management. The joint optimization of these two activities is known as Inventory Routing Problem (IRP). The main objective of IRP is to determine the set of retailers to be delivered to in each period, the delivery sequence for each vehicle, and the quantities of goods delivered to each retailer for each period of a planning horizon. The traditional IRPs are faced different problems, caused mainly by lack of complete and/or timely information such as shifts in demand, traffic caused by a sudden vehicles accident, etc. sharing of updated and reliable logistics information can meaningful improve the efficiency of IRP. Moreover, because of the specificity of IRP in urban logistic, it is important to tack into account other criteria as social, environmental criteria and service level that could be in conflict. The main objective of this thesis is to (i) choose appropriate social, environmental and service level criteria, (ii) integrate them in mathematical models, and (iii) study the impact of these criteria on dynamic optimization of IRPs for perishable products under uncertain parameters. For this purpose, three mathematical models are proposed. The first model is multi-objective mathematical model in order to make a trade-off between service level, environmental criteria and economic. To decrease quantity of expired products, a nonlinear step function as holding cost function is integrated in the model. Moreover, to solve the problem a fuzzy possibilistic approach is applied to handle uncertain parameters. In the second model, a bi-objective mathematical model is proposed to study impact of social issues on the IRPs. In the proposed model, first objective function concerns economic criteria while the second one social issues. A scenario-based stochastic approach is developed to cope with uncertainty in the model. Finally, the third model concerns impact of using real-time information in efficiency of IRPs. It is noteworthy that, according significant role of perishable products in the both financially and ecology sides of IRPs, perishable products are considered in all three proposed model while even proposed models are appropriate to nonperishable ones as well. The results show that a dynamic management is more efficient than the static one

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Guerrero, Rueda William Javier. "Models and optimization methods for the inventory-location-routing problem." Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0002/document.

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Cette thèse considère le problème consistant à intégrer les décisions de routage et stockage lors de la conception de la chaîne logistique. Le but est de sélectionner des dépôts parmi un ensemble de candidats pour desservir un ensemble de détaillants à l’aide d’une ﬂotte de véhicules de capacité permettant visiter plus d’un détaillant par route. On cherche à déterminer la localisation de ces dépôts et les tournées des véhicules aﬁn de maintenir leurs niveaux optimaux de stocks. La demande chez les détaillants est connue à l’avance. Des applications dans les domaines de la logistique humanitaire et militaire sont envisageables. Pour résoudre le problème, deux matheuristiques sont proposées. Dans la première partie, une méthode coopérative qui combine des méthodes exactes pour le problème de conception de la chaîne logistique et des méthodes heuristiques de routage est présentée. Dans la deuxième partie, une méthode de décomposition utilisant une réformulation de Dantzig-Wolf sur les variables de routage est proposée. L’algorithme intègre les concepts de génération de colonnes, relaxation lagrangienne et recherche locale. Les résultats montrent la capacité des algorithmes à trouver des solutions de bonne qualité et nous estimons de façon empirique l’impact de considérer un modèle intégré au lieu d’utiliser une méthode d’optimisation séquentielle. De plus, les résultats des méthodes présentées sur des sous-problèmes sont aussi étudiés. Ces sont: le problème de localisation-routage, le problème de tournées avec gestion de stocks, et le problème de plus court chemin généralisé
The problem of designing a supply chain including simultaneously routing and inventory management decisions is studied in this thesis. The objective is to select a subset of depots to open, the inventory policies for a 2-echelon system, and the set of routes to perform distribution from the upper echelon to the next using a homogeneous ﬂeet of vehicles over a ﬁnite planning horizon. Demand is considered to be known. Applications are found in humanitarian logistics and military logistics. To solve the problem, two matheuristic procedures are developed. On the ﬁrst part a cooperative algorithm combining exact methods for the supply chain design problem and routing heuristics is presented. On the second part, a partition is proposed using a Dantzig-Wolf reformulation on the routing variables. An hybridization between column generation, Lagrangian relaxation and local search is proposed in this part, put together as a heuristic method. Furthermore, results demonstrate the capability of the algorithms to compute high quality solutions and empirically estimate the improvement in the cost function of the proposed model when compared to a sequential optimization approach. Furthermore, results of the proposed methodologies on benchmark instances for subproblems are studied as well. Those are the capacitated location-routing problem, the inventory-routing problem, and the generalized elementary shortest path problem

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Balun, Pairote. "A Stochastic Vendor Managed Inventory Problem and Its Variations." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4987.

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We analyze the problem of distributing units of a product, by a capacitated vehicle, from one storage location (depot) to multiple retailers. The demand processes at the retailers are stochastic and time-dependent. Based on current inventory information, the decision maker decides how many units of the product to deposit at the current retailer, or pick up at the depot, and which location to visit next. We refer to this problem as the stochastic vendor managed inventory (SVMI) problem. In the Markov decision process model of the SVMI problem, we show how a retailer continues to be the vehicle's optimal destination as inventory levels of the retailers vary. Furthermore, an optimal inventory action is shown to have monotone relations with the inventory levels. The multi-period SVMI problem and the infinite horizon (periodic) SVMI problem are analyzed. Additionally, we develop three suboptimal solution procedures, complete a numerical study, and present a case study, which involves a distribution problem at the Coca-Cola Enterprises, Inc. We consider four variations of the SVMI problem, which differ in the available state information and/or the vehicle routing procedure. Analytically, we compare the optimal expected total rewards for the SVMI problem and its variations. Our computational experience suggests a complementary relationship between the quality of state information and the size of the set of retailers that the vehicle can visit.

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MONTEIRO, NATHALIA JUCA. "MULTI-VEHICLES MULTI-PRODUCTS INVENTORY ROUTING PROBLEM WITH TRANSSHIPMENT: A CASE STUDY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=31468@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
O transporte e os estoques correspondem a maior parte dos custos logísticos de uma empresa. Com o avanço da tecnologia, passou-se a analisar em conjunto esses dois componentes e não mais separados, como era feito anteriormente. O Problema de Roteirização de Veículos com Estoque (Inventory Routing Problem – IRP), nasceu dessa análise conjunta e procura encontrar a melhor rota para os veículos, atendendo a um determinado nível de estoque. Este trabalho apresenta um modelo de IRP com múltiplos veículos e produtos, onde existe a possibilidade de transbordo entre os centros de distribuição existentes. O modelo desenvolvido foi elaborado em um estudo de caso real em uma empresa do setor varejista. Após sua elaboração, o modelo foi testado com uma instância menor e comparado a situação atual da empresa, a fim de testar sua eficiência. Em seguida, foi rodado com os dados completos da empresa, e foram analisados os resultados. Na resolução, foi utilizado o software Xpress, o qual utiliza programação inteira como método de resolução.
Transport and inventories account for most of a company s logistics costs. With the advancement of technology, we began to analyze these two components together and no longer separate, as was done previously. The Inventory Routing Problem (IRP) was born from this joint analysis and seeks to find the best route for the vehicles, meeting a certain level of inventory. This work presents an IRP model with multiple vehicles and products, where there is the possibility of transshipment between existing distribution centers. The developed model was elaborated in a real case study in a company of the retail sector. After its elaboration, the model was tested with a smaller instance and compared to the current situation of the company in order to test its efficiency. It was then run with the complete company data, and the results were analyzed. In the resolution, Xpress software was used, which uses integer programming as the resolution method.

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Sajjadi, Seyed Reza. "Integrated supply chain: multi products location routing problem integrated with inventory under stochastic demand." Diss., Wichita State University, 2008. http://hdl.handle.net/10057/2077.

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When two logistical decisions of the supply chain namely location (a strategic decision) and routing (a tactical decision) are combined, the location- routing problem (LRP) is formed. LRP deals with simultaneously locating one or more supply facility among a set (or sets) of potential facilities and assigning customers to the selected facility (or facilities). To further improve the operation of the supply chain process, it is presented in this dissertation to integrate inventory control, as another tactical decision, with the LRP. The presented model considers the multi-product network under the fixed- interval inventory policy where stochastic demands represent the customers' requirements. Moreover, the third party logistics allows excess space for selected warehouses if needed. A two phase heuristic simulated annealing is presented as solution methodology. Test problems are designed and solved by the developed algorithm to evaluate the presented solution approach. Results show that the integrated decision leads to saving on the network cost. Furthermore, two case studies are discussed to show how the presented model can be used in practice
Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering
Includes bibliographic references (leaves 128-135)

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Sajjadi, Seyed Reza Cheraghi Seyed Hossein. "Integrated supply chain : multi products location routing problem integrated with inventory under stochastic demand /." A link to full text of this dissertation in SOAR, 2008. http://hdl.handle.net/10057/2077.

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Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering
"December 2008". Copyright Seyed Reza Sajjadi, 2008. All rights reserved Includes bibliographic references (leaves 128-135).

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Solyali, Oguz. "One-warehouse Multi-retailer Problem Under Inventory Control And Transportation Policies." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12610239/index.pdf.

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We consider a one-warehouse multi-retailer system where the warehouse orders or receives from its supplier and replenishes multiple retailers with direct shipping or multi-stop routing over a finite time horizon. The warehouse has the knowledge of external (deterministic) demands at the retailers and manages their inventories while ensuring no stock-out. We consider two problems with direct shipping policy and two problems with routing policy. For the direct shipping policy, the problem is to determine the optimal replenishments for the warehouse and retailers such that the system-wide costs are minimized. In one problem, the warehouse decides about how much and when to ship to the retailers while in the other problem, inventory level of the retailer has to be raised up to a predetermined level whenever replenished. We propose strong mixed integer programming formulations for these problems. Computational experiments show that our formulations are better than their competitors and are very successful in solving the problems to optimality. For the routing policy, the problem is to decide on when and in what sequence to visit the retailers and how much to ship to a retailer so as to minimize system-wide costs. In one problem, the warehouse receives given amounts from its supplier while in the other the warehouse decides on its own replenishments. We propose branch-and-cut algorithms and heuristics based on strong formulations for both problems. Computational results reveal that our procedures perform better than their competitors in the literature for both problems.

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Farias, de Araújo Katyanne. "Inventory routing problems on two-echelon systems : exact and heuristic methods for the tactical and operational problems." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAI064.

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Les activités de transport et de gestion des stocks ont un impact important les unes sur les autres. Assurer un niveau de stock idéal peut demander des livraisons fréquentes, ce qui entraîne des coûts logistiques élevés. Pour optimiser les compromis entre les coûts de stock et de transport, des systèmes VMI (Vendor Managed Inventory) ont été développés pour gérer ensemble les opérations de stock et de transport. Pour un ensemble de clients ayant des demandes sur un horizon de temps, le problème de détermination des tournées et des quantités à livrer avec un coût minimum de gestion de stock et de transport est connu sous le nom de Inventory Routing Problem (IRP). Les systèmes à deux échelons ont également été étudiés pour améliorer le flux de véhicules dans les zones urbaines. étant donné que des nouvelles politiques de gestion sont apparues, dans le but de limiter le trafic des gros véhicules et leur vitesse dans les centres urbains, des Centres de Distribution (DC) sont mis en place pour coordonner les flux de marchandises à l'intérieur et à l'extérieur des zones urbaines. Les produits sont donc livrés aux clients par les fournisseurs via les DC.Nous proposons de combiner un système à deux échelons avec le IRP. Nous introduisons un Operational Two-Echelon Inventory Routing Problem (O-2E-IRP), ce qui est une nouvelle extension du IRP à notre connaissance. Dans le O-2E-IRP proposé, les clients doivent être servis par un fournisseur strictement via des DC et les tournées doivent être définis dans les deux échelons sur un horizon de temps donné. Trois politiques de réapprovisionnement et de configurations de routage différentes sont modélisées pour ce problème. Nous développons deux formulations mathématiques, ainsi qu'un algorithme Branch-and-Cut (B&C) combiné à une matheuristique pour résoudre le problème. De plus, nous analysons plusieurs inégalités valides disponibles pour le IRP et nous introduisons de nouvelles inégalités valides inhérentes au IRP à deux échelons. Des expériences de calcul approfondies ont été effectuées sur un ensemble d'instances générées de manière aléatoire. Les résultats obtenus montrent que les performances des méthodes sont liées à la politique de stock et à la configuration de routage.Dans le contexte d'un IRP à deux échelons, deux décisions tactiques importantes doivent être prises en plus des décisions de livraison de routage et de quantité de livraison: à partir de quel DC sera fourni chaque client et en utilisant quels véhicules ? Répondre à ces questions est extrêmement difficile car cela implique de pouvoir minimiser les coûts opérationnels d'un système de livraison VMI à deux échelons à long-terme et avec des demandes incertaines. Pour faire face à cela, nous présentons le Tactical Two-Echelon Inventory Routing Problem (T-2E-IRP) qui optimise les décisions en fonction d'un horizon à long-terme et en tenant compte des demandes stochastiques. Trois politiques de gestion des stocks sont modélisées et appliquées à un ou aux deux échelons. Nous développons une approche de simulation pour résoudre le T-2E-IRP sur un horizon de temps à long-terme. Nous proposons quatre formulations et deux algorithmes B&C pour définir l'affectation des clients et des véhicules aux DC en fonction d'un horizon de temps court. Ensuite, nous évaluons ces décisions d'affectation via un outil de simulation qui résout un sous-problème du T-2E-IRP, qui consiste en les décisions de livraisons du fournisseur aux DC et des DC aux clients, sur un horizon glissant. De nombreuses expériences sont effectuées pour un ensemble d'instances générées aléatoirement. L'impact de plusieurs paramètres utilisés pour déterminer l'affectation des clients et des véhicules aux DC sur le coût total est analysé. Basé sur des expériences, nous définissons la combinaison de paramètres qui fournit généralement les meilleurs résultats sur les instances générées
Transport and inventory management activities have a great impact on each other. Ensuring an ideal inventory level can require frequent deliveries, leading to high logistics costs. To optimize the trade-offs between inventory and transportation costs, VMI (Vendor Managed Inventory) systems have been developed to manage inventory and transportation operations together. Given a set of customers with demands over a time horizon, the problem of determining routes and delivery quantities at a minimum inventory holding and transportation costs is known as Inventory Routing Problem (IRP). Two-echelon systems have also been studied to improve the freight vehicle flow inside urban areas. As new management policies have emerged, with the goal of limiting the traffic of large vehicles and their speed in urban centers, Distribution Centers (DC) are introduced to coordinate freight flows inside and outside the urban areas. Products are then delivered from the suppliers to the customers through the DC.We propose to combine a two-echelon system with the IRP. We introduce an Operational Two-Echelon Inventory Routing Problem (O-2E-IRP), which is a new extension of the IRP to the best of our knowledge. On the proposed O-2E-IRP, the customers must be served by a supplier strictly through DC and routes must be defined in both echelons over a given time horizon. Three different replenishment policies and routing configurations are modeled for this problem. We develop two mathematical formulations, and a Branch-and-Cut (B&C) algorithm combined with a matheuristic to solve the problem. In addition, we analyze several valid inequalities available for IRP, and we introduce new ones inherent to the IRP within two echelons. Extensive computational experiments have been carried out on a set of randomly generated instances. The obtained results show that the performance of the methods is related to the inventory policy and routing configuration.In the context of a two-echelon IRP, two important tactical decisions have to be taken in addition to route and quantity delivery decisions: from which DC will be supplied each customer and using which vehicles? Answering these questions is extremely difficult as it implies being able to minimize operational costs for a two-echelon VMI delivery system on long-term and with uncertain demands. In order to deal with this, we introduce the Tactical Two-Echelon Inventory Routing Problem (T-2E-IRP) that optimizes the decisions based on a long-term horizon and considering stochastic demands. Three inventory management policies are modeled and applied at one or both echelons. We develop a simulation approach to solve the T-2E-IRP on a long-term time horizon. We propose four formulations and two B&C algorithms to define the assignment of customers and vehicles to the DC based on a short time horizon. Then, we evaluate these assignment decisions through a simulation tool that solves a subproblem of the T-2E-IRP, which consists of the decisions of deliveries from the supplier to the DC and from the DC to the customers, on a rolling-horizon framework. Extensive computational experiments are performed for a set of randomly generated instances. The impact of several parameters used to determine the assignment of customers and vehicles to DC on the total cost is analyzed. Based on the experiments, we define the combination of parameters that generally provides the best results on the generated instances

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17

He, Yun. "Problèmes de tournée avec prise en compte explicite de la consommation d'énergie." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30165/document.

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Dans le problème de tournées avec gestion de stock ou "Inventory Routing Problem" (IRP), le fournisseur a pour mission de surveiller les niveaux de stock d'un ensemble de clients et gérer leur approvisionnement en prenant simultanément en compte les coûts de transport et de stockage. Etant données les nouvelles exigences de développement durable et de transport écologique, nous étudions l'IRP sous une perspective énergétique, peu de travaux s'étant intéressés à cet aspect. Plus précisément, la thèse identifie les facteurs principaux influençant la consommation d'énergie et évalue les gains potentiels qu'une meilleure planification des approvisionnements permet de réaliser. Un problème relatif à l'approvisionnement en composants de chaînes d'assemblage d'automobiles est tout d'abord considéré pour lequel la masse transportée, la dynamique du véhicule et la distance parcourue sont identifiés comme les principaux facteurs impactant la consommation énergétique. Ce résultat est étendu à l'IRP classique et les gains potentiels en termes d'énergie sont analysés. Un problème industriel de tournées avec gestion de stock est ensuite étudié et résolu, notamment à l'aide d'une méthode de génération de colonnes. Ce problème met en évidence les limitations du modèle IRP classique, ce qui nous a amené à définir un modèle d'IRP plus réaliste. Finalement, une méthode de décomposition basée sur la relaxation lagrangienne est développée pour la résolution de ce problème dans le but de minimiser la consommation énergétique
The thesis studies the Inventory Routing Problem (IRP) with explicit energy consideration. Under the Vendor Managed Inventory (VMI) model, the IRP is an integration of the inventory management and routing, where both inventory storage and transportation costs are taken into account. Under the new sustainability paradigm, green transport and logistics has become an emerging area of study, but few research focus on the ecological aspect of the classical IRP. Since the classical IRP concentrates solely on the economic benefits, it is worth studying under the energy perspective. The thesis gives an estimation of the energetic gain that a better supplying plan can provide. More specifically, this thesis integrates the energy consumption into the decision of the inventory replenishment and routing. It starts with a part supplying problem in car assembly lines, where the transported mass, the vehicle dynamics and the travelled distance are identified as main energy influencing factors. This result is extended to the classical IRP with energy objective to show the potential energy reduction that can be achieved. Then, an industrial challenge of IRP is presented and solved using a column generation approach. This problem put the limitations of the classical IRP model in evidence, which brings us to define a more realistic IRP model on a multigraph. Finally, a Lagrangian relaxation method is presented for solving this new model with the aim of energy minimization

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18

Azuma, Regina Mitsue. "Otimização multiobjetivo em problema de estoque e roteamento gerenciados pelo fornecedor." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259081.

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Orientador: Fernando José Von Zuben
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: A classe de problemas de estoque e roteamento está presente em várias áreas, incluindo indústria automobilística e gerência de numerário no reabastecimento de caixas eletrônicos. Supondo que o fornecedor é responsável pela estocagem e distribuição dos produtos, sujeito a um conjunto de restrições, o desafio que se apresenta é a determinação de uma política ótima, mais especificamente quais clientes atender, qual quantidade a ser fornecida a cada cliente e qual rota empregar visando a minimização dos custos. Este trabalho apresenta uma proposta de solução para uma das mais comuns formulações do problema: um produto é distribuído a partir de um fornecedor para vários clientes em um horizonte de tempo definido. O transporte é realizado por um veículo de capacidade limitada. Para produzir a otimização simultânea de ambos os objetivos, minimização dos custos de transporte e estoque, a proposta segue uma abordagem multiobjetivo e se baseia no uso do algoritmo SPEA2 (do inglês, Strength Pareto Evolutionary Algorithm 2), incluindo inovações na representação de soluções-candidatas, nos operadores genéticos e de busca local. A fronteira de Pareto estimada é então composta de múltiplas soluções não-dominadas, representando compromissos distintos entre custos de transporte e estoque. Como casos de estudo, são tomadas instâncias de médio porte extraídas da literatura e são geradas instâncias de grande porte. Para as instâncias de médio porte, as fronteiras de Pareto estimadas em cada caso são comparadas com as respectivas soluções ótimas da versão mono-objetivo de cada problema, pois já existe um algoritmo exato de solução para a formulação mono-objetivo de instâncias de médio porte
Abstract: The class of inventory routing problems (IRP) is present in several areas, including automotive industry and cash management for ATM networks. Given that the supplier is responsible for managing the product inventory and replenishment, subject to a set of restrictions, the challenge here is to determine an optimal policy, more specifically which retailers to serve, the quantity to deliver to each retailer and which routes to employ in order to minimize the cost. This work presents a proposal to solve one version of the IRP usually found in the scientific literature: a product is distributed from a supplier to several retailers in a defined time horizon. Shipment is performed by a vehicle with limited capacity. To perform the simultaneous optimization of both objectives, minimization of transportation and inventory costs, the proposal follows a multi-objective approach based on SPEA2 (Strength Pareto Evolutionary Algorithm 2), including innovative aspects mainly associated with the representation of candidate solutions, genetic operators and local search. The Pareto front is then composed of multiple non-dominated solutions with distinct trade-offs between transportation and inventory costs. As case studies, medium size instances extracted from the literature are considered and large size instances are generated. For the medium size instances, the estimated Pareto fronts are compared, in each case, with the corresponding optimal solutions associated with the single-objective version of each problem, given that there is already an exact algorithm to solve such medium size single-objective instances
Mestrado
Engenharia de Computação
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19

Alves, Pedro Yuri Araujo Lima. "Problema de estoque e roteirização com demanda estocástica e janelas de tempo: uma abordagem utilizando relaxação lagrangeana." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/100/100131/tde-21052018-152551/.

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Fornecedores necessitam atender a demanda de seus clientes da forma mais adequada possível e mantendo a qualidade de seu serviço, porém em muitos casos essa demanda é desconhecida. Esse problema pode ser modelado como um problema de roteirização e estoque com demanda estocástica o qual inclui o controle de estoque, transporte do produto e decisões de agendamento da entrega. Existem vários trabalhos na literatura para resolver esse problema, porém nenhum deles lida com janela de tempo de atendimento, capacidade máxima de estoque tanto no cliente quanto no depósito e o nível de confiança de atendimento individualizado para cada cliente. O objetivo principal deste trabalho é propor um novo algoritmo baseado em otimização matemática para lidar com esse problema mais realista. Além disso, este trabalho tem como objetivo secundário melhorar o algoritmo de estado da arte baseado em otimização matemática, visando encontrar soluções com um menor tempo computacional e custo. Foram realizados experimentos com instâncias sintéticas com 15 até 50 clientes, as quais são geradas aleatoriamente, e com uma instância real, baseada na experiência profissional no mercado empresarial e em cenários reais de distribuição na cidade de São Paulo
Providers need to supply the demand of their clients as optimally as possible and maintaining the quality of their service, however in many cases this demand is unknown. This problem can be modeled as a inventory routing problem with stochastic demand, which includes inventory control, product transportation and delivery scheduling decisions. There are several papers in the literature to solve this problem, but none of them deals with service time window, maximum stock capacity for both the customer and the depot and individualized confidence level for each costumer. The main objective of this work is to propose a new algorithm based on mathematical optimization to deal with this more realistic problem. In addition, this work has as secondary objective to improve the state of the art algorithm based on mathematical optimization, aiming to find solutions with a lower computational time and cost. Experiments were performed with synthetic instances with 15 to 50 clients, which are randomly generated, and with a real instance, based on professional experience in the business market and in real distribution scenarios in the city of São Paulo

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20

Raimundo, Marcos Medeiros 1988. "Uma extensão para o problema de roteamento e estoque." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259076.

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Orientador: Fernando José Von Zuben
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: O gerenciamento de cadeias de suprimento no mundo corporativo é de grande relevância prática e uma de suas versões é conhecida como problema de roteamento e estoque. Este trabalho propõe uma formulação linear-inteira genérica e flexível para este problema de otimização, assim como uma metodologia de solução. Nesta nova formulação proposta, algumas peculiaridades da rede de suprimentos podem ser especificadas como parâmetros de entrada, permitindo assim que o usuário seja capaz de realizar modificações na estrutura, na hierarquia e no elenco de restrições da cadeia de suprimentos, sem precisar refazer a formulação matemática associada. Com isso, é possível resolver uma grande diversidade de configurações do problema, sem a necessidade de adaptações junto à metodologia de solução. A natureza genérica e flexível da formulação linear-inteira se deve às seguintes propriedades, todas elas passíveis de serem definidas como parâmetros de entrada: (1) Todo nó da rede pode produzir ou consumir produtos; (2) Todo nó da rede pode enviar e receber produtos; (3) Decorrente das propriedades (1) e (2), a hierarquia de entrega fica generalizada, com o produto podendo passar por vários nós antes de ser consumido; (4) Restrições presentes na formulação garantem consistência, por exemplo, entre quantidade de produto entregue pelos fornecedores e recebida pelos consumidores; (5) Restrições presentes na formulação estão associadas a especificações que podem ser ativadas, como intervalo de tempo entre entregas. Os resultados experimentais contemplam soluções para múltiplas configurações do problema, todas representáveis pela formulação proposta e, portanto, todas resolvidas pela mesma metodologia de solução. Essas múltiplas configurações trabalhadas nos experimentos evidenciam os benefícios do emprego de uma formulação estendida para o problema de roteamento e estoque. Além disso, visando comparação com propostas alternativas disponíveis na literatura, tomou-se uma configuração específica e bem-estabelecida do problema, para a qual existe uma formulação própria e uma metodologia de solução dedicada. Neste experimento comparativo, chegou-se às mesmas soluções e, em algumas parametrizações, até a soluções de melhor qualidade
Abstract: Managing supply chains in the corporate world is of great practical relevance and one of its versions is named inventory routing problem. This work proposes a more generic and flexible linear-integer formulation for this optimization problem, together with a solution methodology. In the novel formulation proposed here, some peculiarities of the supply network can be specified as input parameters, thus allowing the user to make modifications to the structure, the hierarchy and the set of constraints in the supply chain, without having to rebuild the associated mathematical formulation. Therefore, it is possible to solve a wide variety of configurations of the problem without the need for adjustments in the solution methodology. The generic and flexible nature of the linear-integer formulation is due to the following properties, all of them being definable as input parameters: (1) Every node of the network can produce or consume products; (2) Every node of the network can send and receive products; (3) Due to properties (1) and (2), the hierarchy of delivery is generalized, with the product being able to pass through several nodes before being consumed; (4) Some restrictions of the formulation ensure consistency, for example, between the amount of product delivered by the suppliers and received by the consumers; (5) Some restrictions of the formulation are associated with specifications that can be activated, as the time interval between deliveries. The experimental results include solutions for multiple configurations of the problem, all representable by the proposed formulation and, as a consequence, all able to be solved by the same solution methodology. Those multiple configurations considered in the experiments highlight the benefits of employing an extended formulation for the inventory routing problem. Aiming at comparing to alternative proposals available in the literature, it was considered a specific and well-established configuration of the problem, for which there are a proper formulation and a dedicated solution methodology. In this comparative experiment, we came to the same solutions and, in some parameterizations, even better solutions
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Engenharia de Computação
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21

Fomundam, Samuel Fomunyam. "Solving continuous replenishment inventory routing problems." College Park, Md.: University of Maryland, 2008. http://hdl.handle.net/1903/8601.

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Thesis (M.S.) -- University of Maryland, College Park, 2008.
Thesis research directed by: Dept. of Mechanical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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22

Rahmouni, Mouna. "Optimisation combinée des approvisionnements et du transport dans une chaine logistique." Thesis, Aix-Marseille, 2015. http://www.theses.fr/2015AIXM4329.

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Le problème d’approvisionnement conjoint (JDP) proposé est un problème de planification des tournées de livraisons sur un horizon de temps décomposé en périodes élémentaires, l’horizon de temps étant la période commune de livraison de tous les produits,. La donnée de ces paramètres permet d’obtenir une formulation linéaire du problème, avec des variables de décision binaires. Le modèle intègre aussi des contraintes de satisfaction de la demande à partir des stocks et des quantités livrées, des contraintes sur les capacités de stockage et de transport.Afin de résoudre aussi le problème de choix des tournées de livraison, il est nécessaire d'introduire dans le modèle des contraintes et des variables liées aux sites visités au cours de chaque tour. Il est proposé de résoudre le problème en deux étapes. La première étape est le calcul hors ligne du coût minimal de la tournée associé à chaque sous-ensemble de sites. On peut observer que pour tout sous-ensemble donné de sites, le cycle hamiltonien optimal reliant ces sites à l'entrepôt peut être calculé à l'avance par un algorithme du problème du voyageur de commerce (TSP). Le but ici n'est pas d'analyser pleinement le TSP, mais plutôt d'intégrer sa solution dans la formulation de JRP. .Dans la deuxième étape, des variables binaires sont associées à chaque tour et à chaque période pour déterminer le sous-ensemble de sites choisi à chaque période et son coût fixe associé
The proposed joint delivery problem (JDP) is a delivery tour planning problem on a time horizon decomposed into elementary periods or rounds, the time horizon being the common delivery period for all products. The data of these parameters provides a linear formulation of the problem, with binary decision variables. The model also incorporates the constraints of meeting demand from stock and the quantities supplied, storage and transport capacity constraints.In order to also solve the problem of choice of delivery rounds, it is necessary to introduce in the model several constraints and variables related to the sites visited during each round. It is proposed to solve the problem in two steps. The first step is the calculation of the minimum off-line cost of the tour associated with each subset of sites. One can observe that for any given subset of sites, the optimal Hamiltonian cycle linking those sites to the warehouse can be calculated in advance by a traveling salesman problem algorithm (TSP). The goal here is not to fully analyze the TSP, but rather to integrate its solution in the formulation of the JRP. In the second stage, binary variables are associated with each subset and each period to determine the selected subset of sites in each period and its associated fixed cost

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23

Moryadee, Chanicha. "Optimisation models and heuristic methods for deterministic and stochastic inventory routing problems." Thesis, University of Portsmouth, 2017. https://researchportal.port.ac.uk/portal/en/theses/optimisation-models-and-heuristic-methods-for-deterministic-and-stochastic-inventory-routing-problems(182ea07e-ef7b-4b4c-85c9-7570e8e5a160).html.

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The inventory routing problem (IRP) integrates two components of supply chain management, namely, inventory management and vehicle routing. These two issues have been traditionally dealt with problems in the area of logistics separately. However, these issues may reduce the total costs in which the integration can lead a greater impact on overall system performance. The IRP is a well-known NP-hard problem in the optimisation research publication. A vehicle direct delivery from the supplier with and without transhipments (Inventory Routing Problem with Transhipment, IRPT) between customers in conjunction with multi-customer routes in order to increase the flexibility of the system. The vehicle is located at a single depot, it has a limited capacity for serving a number of customers. The thesis is focused on the two main aspects: (1) Development of the optimisation models for the deterministic and stochastic demand IRP and IRPT under ML/OU replenishment polices. On the deterministic demand, the supplier deliveries products to customers whose demands are known before the vehicle arrives at the customers’ locations. Nevertheless, the stochastic demand, the supplier serves customers whose actual demands are known only when the vehicle arrives at the customers’ location. (2) Development of integrated heuristic, biased probability and simulation to solve these problems. The proposed approaches are used for solving the optimisation models of these problem in order to minimise the total costs (transportation costs, transhipment costs, penalty costs and inventory holding costs). This thesis proposed five approaches: the CWS heuristic, the Randomised CWS heuristic, the Randomised CWS and IG with local search, the Sim-Randomised CWS, and the Sim-Randomised CWS and IG with local search. Specifically, the proposed approaches are tested for solving the deterministic demand IRP and IRPT, namely, the IRP-based CWS, the IRP-based Randomised CWS, the IRP-based Randomised CWS and IG with local search. For the transhipment case are called the IRPT-based CWS, the IRPT-based Randomised CWS, and the IRP-based Randomised CWS and IG with local search. On the stochastic demand, these proposed approaches are named the SIRP-based Sim-Randomised CWS, the SIRPT-based Sim-Randomised CWS, the SIRP-based Sim-Randomised CWS and IG with local search, and the SIRPT-based Sim-Randomised CWS and IG with local search. The aim of using the sim-heuristic is to deal with stochastic demand IRP and IRPT, the stochastic behaviour is the realistic scenarios in which demand is used to be addressed using simulation. Firstly, the Sim-Randomised CWS approach, an initial solution is generated by Randomised CWS heuristic, thereafter an MCS is combined to provide further improvement in the final solution of the SIRP and the SIRPT. Secondly, the integration of Randomised CWS with MCS and IG with local search is solved on these problems. Using an IG algorithm with local search improved the solution in which it generated by Randomised CWS. The developed heuristic algorithms are experimented in several benchmark instances. Local search has been proven to be an effective technique for obtaining good solutions. In the experiments, this thesis considers the average over the five instances for each combination and the algorithms are compared. Thus, the IG algorithm and local search outperformed the solution of Sim-Randomised CWS heuristics and the best solutions in the literature. This proposed algorithm also shows a shorter computer time than that in the literature. To the best of the author’ knowledge, this is the first study that CWS, Randomised CWS heuristic, Sim-Randomised CWS and IG with local search algorithms are used to solve the deterministic and stochastic demand IRP and IRPT under ML/OU replenishment policies, resulting of knowledge contribution in supply chain and logistics domain.

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24

Shiguemoto, Andre Luis. "Heuristicas para o problema de estoque e roteamento de veiculos." [s.n.], 2004. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260050.

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Orientador: Vinicius Amaral Armentano
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
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Mestrado
Engenharia Eletrica
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25

Chekoubi, Zakaria. "Problème intégré de dimensionnement de lots et de tournées de véhicules avec remanufacturing des produits en fin de vie." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0209.

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Dans une chaîne logistique traditionnelle, les opérations de production, de stockage et de distribution sont traitées séparément en raison de la complexité de la planification conjointe de ces opérations et le manque d'informations partagées entre les parties prenantes. Aujourd'hui, pour faire face à la concurrence féroce que connaît le marché mondial, les entreprises sont obligées de planifier conjointement ces activités afin de bénéficier des avantages économiques et environnementaux engendrés par cette intégration. Parmi les problèmes d’optimisation existants dans la littérature, le problème de la planification intégrée qui optimise conjointement les décisions de production, de gestion des stocks, de distribution et de tournées de véhicules, a récemment fait l'objet d'une attention considérable, malgré sa nature NP-difficile. En effet, ses avantages en termes de synchronisation entre les processus, de réduction des coûts et d’amélioration du niveau de service peuvent être importants. En outre, l’optimisation de ce problème dans le contexte des chaînes logistiques en boucle fermée avec gestion des Produits en Fin de Vie (PFV) conduit au développement de chaînes logistiques de plus en plus durables. De plus, les inquiétudes croissantes sur les enjeux environnementaux liés aux activités industrielles ont conduit à l'émergence de politiques de contrôle des émissions carbone. La prise en compte de ces réglementations peut conduire à un impact positif sur la responsabilité environnementale de l’entreprise. Pour répondre à ces défis, l’objectif de cette thèse consiste à concevoir des modèles et de développer des approches d’optimisation pour résoudre un problème de planification intégrée des opérations de production, de ré-usinage, de stockage et de distribution directe-inverse. Nous avons considéré une chaîne logistique en boucle fermée composée d’une ligne de production de produits neufs, d’une ligne de ré-usinage des PFV retournés, deux stocks pour les produits réutilisables et les PFV à ré-usiner, ainsi que des clients ayant des demandes dynamiques en livraison et en collecte. Le but est de déterminer les quantités optimales à produire, ré-usiner et stocker, ainsi que l’ordre de passage chez les clients afin de satisfaire leurs demandes simultanément en livraison et en collecte, tout en minimisant le coût total dû aux opérations induites. Dans un premier temps, un modèle linéaire en nombres entiers est proposé pour optimiser la chaîne logistique en considérant un ou plusieurs véhicules avec capacité limitée. La deuxième partie de la thèse porte sur le développement d’une heuristique de décomposition à deux phases pour résoudre le modèle intégré étendu. La dernière partie de la thèse est consacrée à l’intégration des émissions du dioxyde de carbone dans les décisions de production, de ré-usinage, de stockage et de distribution et d'étudier le comportement des niveaux d'émissions de carbone dans le cadre de la politique de plafonnement et d'échange de droits d'émission de carbone. Des expérimentations numériques permettent de démontrer l’applicabilité et les limites de nos approches
In a traditional supply chain, production, inventory and distribution operations are treated separately due to the complexity of jointly planning these operations and the lack of information shared among stakeholders. Today, in order to face the fierce competition in the global market, companies are forced to jointly plan these activities in order to benefit from the economic and environmental benefits generated by this integration. Among the optimization problems existing in the literature, the integrated planning problem which jointly optimizes production, inventory management, distribution and vehicle routes decisions, has recently received considerable attention, despite its NP-hardiness. Indeed, its benefits in terms of synchronization between processes, cost reduction and improved service level can be significant. In addition, the optimization of this problem in the context of closed-loop supply chains with End-of-Life Product (EOL) management leads to the development of increasingly sustainable supply chains. Furthermore, growing concerns about environmental issues linked to industrial activities have led to the emergence of policies to control carbon emissions. Taking these regulations into account can have a positive impact on the company's environmental responsibility. To meet these challenges, the objective of this thesis is to design models and develop optimization approaches to solve an integrated planning problem of production, remanufacturing, storage and direct-reverse distribution operations. We considered a closed-loop supply chain consisting of a production line for new products, a remanufacturing line for returned EOL products, two types of inventories for reusable products and EOL ones to be remanufactured, as well as customers with dynamic demands for delivery and pickups. The goal is to determine the optimal amounts to produce, remanufacture and store, as well as the order of visiting customers in order to meet their requests simultaneously for delivery and pickup, while minimizing the total cost due to the involved operations. First, a linear integer model is proposed to optimize the supply chain system by considering one or more vehicles with limited capacity. The second part of the thesis concerns the development of a two-phase decomposition heuristic to solve the extended integrated model. The last part of the thesis is devoted to the integration of carbon dioxide emissions into production, remanufacturing, inventory and distribution decisions and to study the behavior of carbon emission levels in the context of cap-and-trade policy. Numerical experiments make it possible to demonstrate the applicability and the limits of our approaches

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26

Stanzani, Amélia de Lorena. "Roteirização de navios com restrições de estoque na indústria petrolífera : contribuições em modelagem matemática e abordagens de solução." Universidade Federal de São Carlos, 2017. https://repositorio.ufscar.br/handle/ufscar/8791.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Vehicle routing problems occur in many practical situations where the distribution of goods and / or services to different demand points is necessary. In this context, this research aims to study a ship routing and scheduling problem that arises at the collection and delivery operations of different types of crude oil from offshore platforms to coastal terminals. In the paradigm adopted for the representation of the problem, the transportation is largely the result of the need to maintain inventories at each supply point (platforms) between minimum and maximum levels, considering production rates on these operating points and the demand attendance of each product in the coastal terminals. The routing and scheduling of the fleet aims to achieve minimum variable cost solutions, and considers various operational constraints, such as the maximum cargo volume transported on each ship, the ships mooring in the operational points ports, the simultaneous unloading of the ships in terminals with more than one berth, among many others. In this research, Inventory Constrained Routing Problem (ICRP) models in the maritime context have been modified and extended for appropriately representating and solving real problems based on data collected in a case study performed on a Brazilian oil company, involving relatively short distances and time horizons. Small sized instances are solved by a mathematical programming software. Given the difficulties of solving larger examples, this study proposes a multistart heuristic method that includes a metaheuristic GRASP and improvement procedures, and also a rolling horizon heuristic. Both methods provide feasible good quality solutions in reasonable computing times. In order to improve the quality of the solutions found by these constructive methods, it is also discussed a procedure that combines the mathematical programming software and local search heuristic methods (matheuristic). The results show the potential of the proposed models and solution methods to tackle the problem and produce competitive solutions.
Problemas de roteirização de veículos ocorrem em diversas situações práticas onde se faz necessária a distribuição de bens e/ou serviços a pontos dispersos de demanda. Nesse contexto, a presente pesquisa visa o estudo de um problema de roteirização e programação de navios presente em operações de coleta e entrega de diferentes tipos de óleo cru de diversas plataformas offshore para vários terminais costeiros. No paradigma adotado para representação do problema, o transporte dos produtos é em grande parte o resultado da necessidade de manutenção dos estoques em cada ponto de suprimento (plataformas) entre níveis mínimos e máximos, considerando-se as taxas de produção nesses pontos operacionais, assim como o atendimento da demanda de cada produto nos terminais costeiros para abastecer as refinarias. A roteirização e programação da frota visa a obtenção de soluções de mínimo custo variável e considera várias restrições operacionais, tais como o volume máximo de carga transportada em cada navio, a viabilidade de atracação de navios em portos dos pontos operacionais, os descarregamentos simultâneos de navios em terminais com mais de um berço, dentre várias outras. Nesse sentido, modelos de otimização da literatura de roteirização veículos com restrições de estoque (Inventory Constrained Routing Problem – ICRP) no contexto marítimo foram modificados e estendidos para representação do problema e resolução de exemplares de uma situação real, definidos a partir de dados coletados em um estudo de caso realizado em uma empresa petrolífera nacional, envolvendo distâncias relativamente curtas e com horizontes de planejamento de curto prazo (poucas semanas). Exemplares de pequeno porte são resolvidos por meio da utilização de um software de programação matemática. Dada a dificuldade de resolução dos exemplos de maior porte, é proposto um método heurístico de múltiplos reinícios composto por uma metaheurística GRASP e procedimentos de melhoria, além de uma heurística de horizonte rolante, que proporcionaram a obtenção de soluções factíveis de boa qualidade em tempos computacionais aceitáveis. Com intuito de melhorar a qualidade das soluções encontradas pelos métodos construtivos, é também discutido um procedimento que combina o software de programação matemática e métodos heurísticos com busca local (mateheurística). Os resultados mostram o potencial dos modelos e métodos de solução aqui desenvolvidos e propostos para abordar o problema e produzir soluções competitivas em relação às soluções da empresa.

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27

Mjirda, Anis. "Recherche à voisinage variable pour des problèmes de routage avec ou sans gestion de stock." Thesis, Valenciennes, 2014. http://www.theses.fr/2014VALE0023/document.

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Dans cette thèse nous nous intéressons à l'étude et à la résolution de problèmes d'optimisation dans le domaine du transport. La première problématique concerne le problème d'élaboration de tournées avec gestion des stocks, et nous considérons dans une seconde partie le problème du voyageur de commerce avec tirant d'eau. Nous avons développé des approches basées sur la recherche à voisinage variable pour résoudre ces problèmes NP-Difficiles, en proposant différentes structures de voisinages et schémas de résolution efficaces. L'évaluation globale des approches proposées sur des instances de la littérature montre leur efficacité. En particulier, nos algorithmes ont amélioré les résultats obtenus par les meilleures approches existantes pour ces deux problèmes
This thesis deals with the study of optimization problems in the transportation domain. We first address the inventory routing problem and we consider the traveling salesman problem with draft limits in a second part. In both cases we have developed methods based on the variable neighborhood search to solve these NP-hard problems. We have proposed several efficient neighborhood structures and solving frameworks. The global evaluation of the proposed approach on sets of benchmarks available in the litterature shows a remarkable efficency and effectiveness. In particular, our algorithms have improved the results obtained by the current best approaches for these two problems

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28

Fernandes, António Silva. "Optimization Algorithms for the Inventory Routing Problem." Master's thesis, 2016. https://repositorio-aberto.up.pt/handle/10216/112235.

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At this point there are already three variants of optimization algorithms, oriented at the Inventory Routing Problem, based on the GRASP metaheuristic capable of solving instances of one vehicle and one product with reasonable GAP and multi products one vehicle with more GAP than desired for most of the instances. The algorithms were developed in c++ and are being compared with a benchmark for the Multi-vehicle Multi-product Inventory Routing Problem. Tests are being made to access computational times affinity with solution improvement. The developed work is within the planned schedule able to consult at http://gnomo.fe.up.pt/~ee10089/SIEM/

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29

Liu, Yi-Ching, and 劉奕青. "The Inventory Routing Problem for Vending Machines." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/82066833502487704884.

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碩士
元智大學
工業工程與管理學系
91
Vendor managed inventory (VMI) refers to a situation in which a supplier manages the inventory replenishment of its customers. The core problem when we implement the VMI is the inventory routing problem (IRP). Three decisions have to be made for IRP: 1) when to serve a customer? 2) how much to deliver to a customer when it is served? and 3) which delivery routes to use? IRP addresses the coordination of inventory replenishment and vehicle routing decisions and is a very complex problem because the solutions of the three sub-problems are interrelated. The replenishment and delivery problem for vending machine is an example of IRP. In this research we consider a service region that a driver delivers products during a given M-day period. The vending machines are typically required to be visited once or several times over the period, and once a day at the most. The days of visits must follow one of the allowable visit-day patterns that were built based on stationary-interval inventory property. The objective of the problem is to minimize the system-wide cost consisting of inventory, stockout and transportation costs subject to the vehicle capacity and vending machine capacities constraints. Three sub-problems are considered in this research: 1) visit-day pattern assignment, 2) vehicle routing problem, and 3) product loading problem. The first two sub-problems can be treated as period vehicle routing problem (PVRP). Since IRP is an NP-hard optimization problem, an exact solution approach would most likely be very time-consuming. We propose a simulated annealing (SA) heuristic solves the IRP in a reasonable time and produces high-quality solutions. We start by assigning an allowable day combination to each customer and then solve a classical VRP for each day of the M-day period. Of course, the two phases of this type of solution approach will interact with each other. The overall scheme was tested on data sets collected from a local soft drink vending machine distributor. Two months data, June and July of 2002, are analyzed by comparing the proposed heuristic against the current delivery pattern. The results show that our heuristic provides better system-wide cost. The new delivery plan can save the total cost up to NT$1326.51/week (22.41%). Based on the collected data, a simulation model is also developed to mimic the demand distribution of each product for each vending machine. The proposed heuristic shows its robustness on the simulation results with cost saving by up to 20.77%.

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30

Fernandes, António Silva. "Optimization Algorithms for the Inventory Routing Problem." Dissertação, 2016. https://repositorio-aberto.up.pt/handle/10216/112235.

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At this point there are already three variants of optimization algorithms, oriented at the Inventory Routing Problem, based on the GRASP metaheuristic capable of solving instances of one vehicle and one product with reasonable GAP and multi products one vehicle with more GAP than desired for most of the instances. The algorithms were developed in c++ and are being compared with a benchmark for the Multi-vehicle Multi-product Inventory Routing Problem. Tests are being made to access computational times affinity with solution improvement. The developed work is within the planned schedule able to consult at http://gnomo.fe.up.pt/~ee10089/SIEM/

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31

"THE INVENTORY ROUTING PROBLEM WITH DETERMINISTIC ORDER-UP-TO LEVEL INVENTORY POLICIES." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606444/index.pdf.

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32

Yuan-Hao, Tsai, and 蔡元皓. "Solving Multi-product Inventory Routing Problem with Split Delivery." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/30605515258472659205.

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碩士
國立雲林科技大學
工業工程與管理系
102
We address the multi-product inventory routing problem in a one-depot and many- customer distribution system in a finite time period while split delivery is considered. The inventory routing problem can be described as the combination of vehicle routing and inventory management problems (Coelho et al. 2014), which are traditionally managed by different departments in a supply chain in spite of knowing the trade-off relationship between them. Coordinating the two important parts in the supply chain can increase overall profit. Besides, vehicle capacity can be used more efficiently by split delivery. This means fewer vehicles using and less traveling distance. Our objective is to minimize the overall cost, including inventory holding cost and transportation cost where the delivery schedule and the shipping quantity of each product for each customer is decided simultaneously. We first construct a mathematical model and test it by Lingo 11.0. Then an algorithm with Genetic Algorithm (GA) concept and variable neighborhood Tabu search is proposed for large-scale instances. Furthermore the ratio of mean daily demand to vehicle capacity and unit holding cost are for sensitivity analysis of split delivery. Computational result shows that the proposed algorithm can solve the multi-product inventory routing problem with split delivery effectively. When the demand has a normal distribution and the ratio of mean daily demand to vehicle capacity is 0.55, split delivery can reach the best profit. And the higher unit holding cost is, the worse the effect of split delivery is.

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bine, yu gin, and 余進彬. "A Real-Time Inventory Routing Problem with Weight Strategy." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/05248733380901835084.

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碩士
大葉大學
工業工程與科技管理學系
96
In recent years, due to the oil crisis and oil supply shortage, the price of oil repeatedly hit new record highs. Among all the business sectors, especially the transportation industry has been facing severe impacts due to its high demand of oil. Hence, while satisfying the clients' demand, reducing the total transportation costs has become the most urgent issue for the supply system of the transportation industry. Cutting costs in the supply chain can be achieved by the two aspects: (1) lowering the distribution costs on the supply side, (2) reducing the inventory and shortage costs on the demand side. We extended one commonly discussed topic in supply chain planning and management called Inventory Routing Problem (IRP) where both inventory and routing path control are monitored simultaneously. The purpose of IRP is to minimize distribution and total inventory costs by directing the delivery quantity and the shipping path in a certain transportation service region. We used IRP to model the circumstance under study. However, IRP models did not consider the difference of weights and the dynamic characteristic of the customers' demand after the vehicle departed, This study proposed a heuristic for determine delivery quantity and the shipping path for the distributor center which uses one single vehicle to serve multiple retailers by considering the weights of each retailer on a real-time basis. Through system simulation, the proposed distribution scheme was shown more cost effective than the conventional distribution schemes. The contribution of research includes taking account of dynamics of IRP and considering weights of the retailers; that can be more reflective on the real-world circumstance.

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34

Li, Wei-Ting, and 李韋廷. "A Study of the Inventory Routing Problem with Time Windows." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/90265742382717787078.

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碩士
國立屏東科技大學
資訊管理系所
97
The Vehicle Routing Problem with Time Windows (VRPTW), an extension of the VRP, had been applied to improve many real-world logistics and distribution problems. Since the VRPTW does not resolve the inventory decision in past references, the time windows and routing will influence each other, so do inventory. So a mathematic model of inventory routing problem with time windows (IRPTW) is proposed. Due that the computational complexity of IRPTW is NP-hard problem, this paper develops a hybrid heuristic algorithm, which integrates the tabu search (TS) and large neighborhood search (LNS) with the implementation techniques of traditional local search algorithms, to solve the IRPTW. This paper compares the heuristic method proposed by this study with the heuristic methods proposed by Kang et al. (2008). The experimental results indicate the IRPTW can assess the logistic costs better than other the methods.

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35

William and 何明蔚. "The Optimization of Vehicle Routing Problem for Carbon Footprint Inventory." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/56395992716770547524.

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碩士
明新科技大學
工業工程與管理研究所
99
Huge amounts of energy resources usage brings the result of global climate abnormality, it has became a practical factor from science research. Both Eco-Design Requirements for Energy-using Products which was noticed in 2007 and Climate Conference in Copenhagen which involved many countries in 2010 appeal the method of carbon emission deduction. Only if knowing direct and indirect self activities that allows to carry out a follow-up carbon emission deduction. The carbon emission which is produced by activities is measured by LCI（Life Cycle Inventory）and LCA（Life Cycle Assessment）. However, there is a significant difference between the secondary data before actual estimating and the primary data after; furthermore it uses substantial human resources, material, cost and time, therefore networking product here as the research object applys integer linear programming into routing problem and develops a best decision-making model in this dissertation. Conclude the LCI data results, through goal function and decision variable from mathematical model to figure the lowest cost and the best path between each supplier. The main purpose is to solve the carbon gap which is caused between secondary data and primary data when examining, moreover, to achieve the best path when checking each step of LCI, the most efficient and the lowest cost decision-making method, a goal of time-saving and carbon footprint calculation efficiency improvement. It is expected in this research to get the result of optimizing the LCI examination procedure, simplifying the back-end analysis, and reducing the complexity, so that apply to other industries.

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36

Widjaja, Audrey Tedja, and 潘月芳. "Simulated Annealing for the Multi-Vehicle Cyclic Inventory Routing Problem." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/89azbc.

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碩士
國立臺灣科技大學
工業管理系
107
This research proposes a new variant of the cyclic inventory routing problem (CIRP) called multi-vehicle CIRP (MV-CIRP). In this problem, there is more than one vehicle available at the supplier site to deliver shipments to customers, and it is not mandatory for the supplier to service all customers. Therefore, a reward is received from each visited customer. Due to the cyclic nature of this problem, the planning horizon is infinite. Thus, the objectives are to find a subset of customers to visit, replenishment quantities and time for each of these customers, and the corresponding vehicle routes for each vehicle such that long-term transportation and inventory costs are minimized and the collected rewards are maximized simultaneously. In order to solve the problem, we develop a mathematical programming model and propose a simulated annealing (SA) algorithm. The proposed SA is tested on the single-vehicle CIRP (SV-CIRP) datasets. Our proposed SA finds 22 optimal solutions and 15 new best solutions out of 50 test problems. When solving MV-CIRP datasets, SA outperforms BARON and the local search algorithm.

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37

Wu, Shang-Hung, and 吳尚鴻. "A study of Location Routing Problem - Considering Multi-period Inventory Cost." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/05717297552012868309.

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碩士
國立雲林科技大學
工業工程與管理研究所碩士班
99
Due to the rapid development of the logistics industry, enterprises in order to avoid the bad impact of product quality and delivery time, they need to integrate the external logistic centers. Inventory in logistic centers help to reduce the transportation cost. Therefore, this study will explore the multi-period, three-level, and two-stage location routing problem. The potential logistic centers are also evaluated at the same time. The proposed solution algorithm includes (1) construct an initial routing, (2) using the selection mechanism to find a suitable logistic center, (3) using the routing exchanges to find a better vehicle routing, (4) Setting up inventory level for each planning period. Finally, the solution algorithm is illustrated by testing examples. A sensitivity analysis is conducted, which include: (1) changing vehicle capacity (2) changing unit inventory cost, (3) changing start-up cost of logistic center. The result shows increasing inventory cost increasing vehicle capacity can effectively reduce the overall cost.

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38

Lee, Shun-Pin, and 李順斌. "A Combined Location-Routing and Inventory Problem in a Distribution System." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/77159870338264455325.

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碩士
國立屏東科技大學
資訊管理系
90
Most literature for location-routing problems in a logistic distribution system or a supply chain is based on the criterion of minimizing transportation costs. The researches on this area focus on estimating distances about these paths and consider minimum costs related to its corresponding traveling cost. However, inventory costs are important and always neglected. It may result in a biased location choice and total cost will increase further. Thus, inventory control and location-routing problem shall be considered together to achieve the lowest total cost. In this paper, a mathematical model for the location-inventory-routing problem is proposed. Since the solution for this model is NP (non-polynomial) problem, we propose several heuristic models to solve the problem. The objective is to minimize the total costs among facility location, inventory and transportation. The results show the proposed method is better than those existing methods based on the total cost criterion. A sensitivity analysis for several parameters is also conducted in this research.

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39

Chung, Chich-Hung, and 鍾志鴻. "A Heuristic method for Vehicle Routing Problem with Backhauls and Inventory." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/06779893560497668857.

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碩士
國立屏東科技大學
資訊管理系所
95
The purpose of this study is to resolve the inventory control decision since the regular vehicle routing problem with backhauls (VRPB) does not, so a mathematic model of vehicle routing problem with backhauls and inventory (VRPBI) is proposed. Because this problem is a NP-Hard problem, this paper proposes a hybrid heuristic algorithm, variable neighborhood tabu search, and adopts six local searches to obtain the global solution. This paper compares the heuristic method proposed by this study with the two heuristic methods proposed by Bianchessi and Righini (2007) and Crispim and Brandao (2005), and six models. The experimental results indicate the VRPBI can be completed in less CPU time and assess the logistic costs better than other the methods.

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40

Lin, Chun-Chih, and 林俊志. "A Heuristic Method for the Combined Location Routing and Inventory Problem." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/59242257703759365556.

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碩士
國立屏東科技大學
資訊管理系
91
The combined location routing and inventory problem is to allocate depots from several potential locations, to schedule vehicles’ routes to meet customers’ demands, and to determine the inventory policy based on the information of customers’ demands, in order to minimize the total system cost. Since finding the optimal solution(s) for this problem is an NP (non-polynomial) problem, we propose a hybrid heuristic models incorporating tabu search (TS) into simulate annealing (SA) to solve the problem. The objective is to minimize the total costs among facility location, inventory and transportation. The results show the proposed method is better than those existing methods based on the total cost criterion. An analysis for several parameters is also conducted in this research.

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41

Chen, An-Zuo, and 陳岸佐. "A flexible model and heuristics for the cyclic inventory routing problem." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/25637624228255022927.

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碩士
國立屏東科技大學
資訊管理系所
98
The purpose of this paper is to determine the route of the vehicle routing problem (VRP), inventory problem and flexible model and heuristics. The inventory-routing problem (IRP) with flexible model and heuristics considers inventory control and vehicle routing decision simultaneously and can reduce the cost of the logistics system significantly. However, flexible model will affect inventory cost and routing cost. Since finding the optimal solutions for CIRP is a NP-hard problem, this paper proposes a flexible heuristics method, variable neighborhood search (VNS), adopting five neighborhood and local search to obtain optimal solution. Our solution could reduce supply chain costs compared with the past.

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42

Li, Hong-Shuo, and 李泓碩. "Using a Hybrid Particle Swarm Optimization Method for the Inventory Routing Problem." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/57378621925109869690.

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碩士
國立屏東科技大學
資訊管理系所
101
The inventory routing problem belongs to NP-hard problems, it is not easy to get the optimal solution. Therefore, in order to get the optimal solution. That is necessary to use heuristic algorithms to calculate in medium or large problem size. On the basis of reference documents and past studies, the investigators found out that using particle swarm optimization algorithm(PSO) in Travelling Salesman Problem(TSP),Vehicle Routing Problem(VRP) and Open Location Routing Problem(OLRP) to solve the path combination is the best way. In consequence, I used Particle Swarm Optimization Algorithm as a foundation to develop the structure of algorithms and we combined the hybrid Large Neighborhood Search(LNS) to ameliorate the disadvantage: (1) fast convergence and (2) fall into regional solutions in Particle Swarm Optimization Algorithm. Then, we developed a hybrid algorithm to plan optimal path combination and transport cycle to make cost minimization in inventory routing problem. The results of this study shows the hybrid particle swarm optimization algorithm’s cost is 2.41% better than particle swarm optimization algorithm in the small size problem, and in the big size problem the cost is 1.84%. The results showed a good performance to use hybrid algorithm in inventory routing problem in my study.

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43

Chiang, Tsung-Han, and 蔣宗翰. "A tabu search algorithm for the open inventory routing problem with time windows." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/10442624953190659836.

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碩士
國立臺灣科技大學
工業管理系
101
The open vehicle routing problem (OVRP) is one of the extensions of the vehicle routing problem (VRP). The original VRP concerns a closed loop problem in which all the routes start and end in the same depot. On the other hand, the OVRP is an open loop problem in which each vehicle starts from a depot, but ends at a final served customer. The applications of OVRP include school bus, train service, and third party logistics. In this research we incorporate the inventory effect into a routing decision, consider the time-window situation in our life and then define a new problem called the open inventory routing problem with time window (OIRPTW). This research presents a mathematical model and algorithm of the OIRPTW based on tabu search (TS). The objective of the OIRPTW is to minimize the sum of the total transportation costs, inventory costs and penalty item of time-window constraint.

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44

Wirdianto, E., Hong Sheng Qi, and M. Khurshid Khan. "Simulation Model of Maritime Inventory Routing Problem with Particular Application to Cement Distribution." 2011. http://hdl.handle.net/10454/8044.

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yes
Simulation is undoubtedly a very useful tool for modelling a system specifically in the presence of stochastic elements and complex interactions between the system entities. In this paper, a simulation model to support decision making in ship scheduling for Maritime Inventory Routing Problem (MIRP) with particular application to cement distribution is presented. The system under study is a combined discrete and continuous system, where a heterogeneous fleet of ships with various sizes and types of contracts transport bulk cement products from production facility (Central Supply, CS) of a cement company to its packing plants (Distribution Centres, DCs). The simulation model in this study has been designed and developed thoroughly to emulate the complexity of the real system of the MIRP. The simulation model has demonstrated the capability to provide support for decision making in ship scheduling of the heterogeneous shipping fleet in the following forms: (a) real time states of inventory levels at CS and DCs and (b) ships’ routing. In addition, one of the main strength of this simulation model is its flexibility. It can be easily expanded or adjusted to different size of system entities for example number of CSs, DCs, berths, vessels, and products.
Support for this research is provided by the Directorate of Higher Education, Ministry of National Education, Republic of Indonesia

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45

羅文韋. "Metaheuristic for Multi-Plant Order Allocation and Ship Routing Problem under Factory`s Inventory Restricted." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/22672609433592786408.

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46

HUNG, WEI-TE, and 洪維德. "A Study of Inventory Routing Problem with Simultaneous Pickup and Delivery in Fresh Distribution Consideration." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/ba3nrd.

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碩士
國立雲林科技大學
工業工程與管理系
106
Inventory Route Problems (IRPs) can be considered as an extending application of Vehicle Routing Problems (VRPs). In general, IRPs considers the factors of inventory management. Decision makers have to arrange not only the route but also when and how much to delivery. In order to save the inventory cost and increase the times of distribution would multiply the transportation cost. In the other hand, to decrease the transportation cost and delivery amount of goods in one time would cause the raising of the inventory cost. Consequently, through the accurate way to combine both the distribution and inventory planning could advance benefit of the whole supply chain system. So as to make the company become more competitively. As time progresses, the need of fresh delivery has become much more than before. Including of convenience stores, supermarket and mall, there are more and more different kinds of fresh goods in these distributors and retailers. Even though the online stores add the fresh delivery service by the electronic commerce. A growing number of the enterprises enter into this area in recent years. Our research combined both fresh delivery and IRPs. Moreover, to make sure the research more like the actual distribution situation, we considered the reusable characteristic of logistics boxes. Therefore we added the pickups and delivers condition in our research. Next, we constructed a model for our problem and let the minimum cost for measurable indicators. Then, we developed a Particle Swarm Optimization algorithm for solving our problem. Last but not least, we used different size of example to test our model and algorithm. Due to the result of the research, in case of rental the medium or small refrigerated trucks, distribute in short way with multiple times would be suitable for fresh delivery. Furthermore, the capacity of the trucks has intense influence for the decayed delivery cost.

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47

Jyun-Ruei, Chen, and 陳俊瑞. "A Study of the Integrated Pricing and Inventory-Routing Problem in a Two-Echelon Supply Chain." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/92355026449721130375.

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碩士
國立屏東科技大學
資訊管理系所
97
The purpose of this paper is to determine the route of the vehicle routing problem (VRP) and inventory problem and pricing. The inventory-routing problem (IRP) in the VMI setting considers inventory control and vehicle routing decision simultaneously and can reduce the cost of the logistics system significantly. However, pricing will affect sale quantity and sale quantity will affect inventory. Therefore, a mathematical model of pricing inventory routing problem (PIRP) is proposed. Since finding the optimal solutions for PIRP is a NP-hard problem, this paper proposes a heuristic method, tabu variable large neighborhood search (TVLNS), adopting two large neighborhood to obtain optimal solution.

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48

Hsu, Wen-Hsuan, and 許文軒. "A Decision Support System of Inventory Routing Problem with Simultaneous Pickup and Delivery Concerning Carbon Footprint." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/32944597614297643969.

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碩士
龍華科技大學
資訊管理系碩士班
103
Most literatures of Inventory-Routing problems find the solutions by simulation, rather than solve the real case problem of logistics firms. Furthermore, few of them consider pickup and delivery problems at the same time. A green logistic issue is also incorporated into the model by considering the interrelationship between the transportation cost and the greenhouse gas emission level. Therefore, this research applies a real publishing logistics firm’s operating data to study the Inventory-Routing problem with simultaneous pickup and delivery concerninig carbon footprint(IRPSPDCF). We develop a decision support system (DSS) to combine the google map module and related logictics information to solve the proposed IRPSPDCF.The mathematical model for IRPSPDCF is first constructed, then Savings method, 2-opt heuristic methods, and 1-1 interchange method are applied to obtain the initial feasible solution, finally Genetic Algorithm(GA) is implemented to find the optimal solution. The numerical examples are illustrated by applying this publishing logistics firm’s real operating data to acquire the optimal delivery routes, and the related economic order quantities, the optimal reorder points and the customer service levels of the retail stores located in those proposed routes. Furthermore, the performance of this proposed method is compared with Savings method, heuristic approach, and current routing planning implemented by this specific logistics company.Finally, the sensitivity analysis is also conducted based on different parameters include vehicle capacity, inventory carrying cost percentage,unit ordering cost,unit shortage cost,unit transport cost,unit returning cost.The proposed decision support system is showed to be very promising in many aspects and helpful to this logistics company for their future planning.

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49

Yu-ShanHsu and 許瑜珊. "A Heuristic Algorithm for Pickups and Deliveries of Inventory Routing Problem among Stores with Perishable Products." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/43v5c5.

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50

Gao, Shih-Jie, and 高識傑. "A Web Logistics Distribution Decision Support Systems for Green Inventory Routing Problem with Simultaneous Pickup and Delivery." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/qu846f.

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碩士
龍華科技大學
資訊管理系碩士班
106
Most publishing logistics firms in Taiwan decide their distributed routes by considering the inventory related cost and transportation cost independently based on their past intuitive experiences. In fact, by concerning both of them, it is more likely to plan the delivered routes economically and efficiently. Due to the increasing environmental concern by the whole world, this total inventorty routing cost better accounts for Greenhouse gas emission cost regarding global warming. Most literatures of Inventory-Routing problems find the solutions by simulation, rather than solve the real case problem of logistics firms. Furthermore, few of them consider pickup and delivery problems at the same time. Due to environmental awareness, carbon emission cost is also incorporated into the model by considering the interrelationship between the transportation cost and Greenhouse gas emission level. Therefore, this research develops a decision support system to the Green Inventory Routing Problem with Simultaneous Pickup and Delivery (GIRPSPD) and to show the planned routes on GoogleMap. The mathematical model for GIRPSPD is first constructed, then Savings method is applied to obtain the initial feasible solution, finally implement Target insert heuristic method and Target exchange heuristic method to find the optimal solution. The numerical examples will be illustrated by applying this publishing logistics firm’s actual operating data to acquire the optimal delivery routes, and the related economic order quantities, the optimal reorder points and customer service levels of the retail stores located in those proposed routes. Furthermore, the performance of two proposed Target heuristic methods will be compared with Savings method and current routing planning implemented by this specific logistics company. Finally, sensitivity analyses are also conducted based on the parameters including truck loading capacity, inventory carrying cost percentages, unit shortage costs, unit ordering costs, unit ordering costs, and unit transport costs to simulate the optimal distribution system design regarding the total inventoy routing cost and GHG emission level. Consequently, the outcomes of this proposed decision support system to GIRPSPD not only have important theoretical contribution, but also provide pratical application applications for the proposed logistics publishing firm’s distribution system design.

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