Relevant bibliographies by topics / Inventory routing problem

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Inventory routing problem'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 January 2023

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Journal articles on the topic "Inventory routing problem"

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Yang, Xianfeng, and Lei Feng. "Inventory Routing Problem." Transportation Research Record: Journal of the Transportation Research Board 2378, no. 1 (January 2013): 32–42. http://dx.doi.org/10.3141/2378-04.

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Aydın, Nevin. "A Genetic Algorithm on Inventory Routing Problem." EMAJ: Emerging Markets Journal 3, no. 3 (March 5, 2014): 59–66. http://dx.doi.org/10.5195/emaj.2014.31.

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Inventory routing problem can be defined as forming the routes to serve to the retailers from the manufacturer, deciding on the quantity of the shipment to the retailers and deciding on the timing of the replenishments. The difference of inventory routing problems from vehicle routing problems is the consideration of the inventory positions of retailers and supplier, and making the decision accordingly. Inventory routing problems are complex in nature and they can be solved either theoretically or using a heuristics method. Metaheuristics is an emerging class of heuristics that can be applied to combinatorial optimization problems. In this paper, we provide the relationship between vendor-managed inventory and inventory routing problem. The proposed genetic for solving vehicle routing problem is described in detail.
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Kazemi, Seyed Mahmood, Masoud Rabbani, Reza Tavakkoli-Moghaddam, and Farid Abolhassani Shahreza. "Blood inventory-routing problem under uncertainty." Journal of Intelligent & Fuzzy Systems 32, no. 1 (January 13, 2017): 467–81. http://dx.doi.org/10.3233/jifs-152175.

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Archetti, Claudia, Nicola Bianchessi, Stefan Irnich, and M. Grazia Speranza. "Formulations for an inventory routing problem." International Transactions in Operational Research 21, no. 3 (February 5, 2014): 353–74. http://dx.doi.org/10.1111/itor.12076.

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Coelho, Leandro C., Jean-François Cordeau, and Gilbert Laporte. "The inventory-routing problem with transshipment." Computers & Operations Research 39, no. 11 (November 2012): 2537–48. http://dx.doi.org/10.1016/j.cor.2011.12.020.

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Lei, Jun Cheng, Yan Peng Wu, and Wen Fei Zeng. "Optimization Approach for Multi-Stork Inventory Routing Problem." Advanced Materials Research 268-270 (July 2011): 1637–40. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.1637.

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Inventory routing problem is one of the key issues to achieve integrated management of logistics. Solving this problem effectively, we can improve vehicle utilization, and reduce distribution costs. This paper, concerning the problem in inventory routing of multi-variety, multi-vendor to multi-customers, proposed heuristic algorithm based on greedy rules. The core strategy of the algorithm is to choose circularly the current lowest unit cost routine ---Hamilton delivery routes. Simulation shows that the algorithm reduces the unloaded ratio of truck, raises the efficiency of truck delivery and saves transport costs.
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Diabat, Ali, Claudia Archetti, and Waleed Najy. "The Fixed-Partition Policy Inventory Routing Problem." Transportation Science 55, no. 2 (March 2021): 353–70. http://dx.doi.org/10.1287/trsc.2020.1019.

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In this paper, we formally introduce a variant of the inventory routing problem (IRP) that we call the fixed-partition policy IRP (FPP-IRP). In contrast to the classical IRP in which delivery routes are arbitrary, the FPP-IRP partitions customers into mutually exclusive clusters that are fixed throughout the optimization horizon, and distribution is performed separately for each cluster. By restricting the flexibility inherent in the classical IRP, the FPP-IRP attains many potential advantages. First, partitioning reduces the operational complexity of the system and allows a simpler organization of the distribution service. Second, it improves the robustness of the system by isolating disruptions to affected clusters. Third, it can fit the needs and requirements of specific applications in which consistency in the distribution policy, such as familiarity between customers and drivers and route invariance, is required. We present two fixed-partition policies for the IRP together with mathematical formulations and valid inequalities. We also present a worst-case analysis on the performance of these policies. Extensive computational results are presented to show the behavior of these policies and glean insights into their potential benefits.
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Aziz, Nur Arina Bazilah, and Choong Jing Yee. "Inventory Routing Problem with Carbon Emission Consideration." MATEMATIKA 35, no. 1 (April 1, 2019): 39–49. http://dx.doi.org/10.11113/matematika.v35.n1.1127.

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Inventory Routing Problem (IRP) has been continuously developed and improved due to pressure from global warming issue particularly related to greenhouse gases (GHGs) emission. The burning of fossil fuel for transportations such as cars, trucks, ships, trains, and planes primarily emits GHGs. Carbon dioxide (CO2) from burning of fossil fuel to power transportation and industrial process is the largest contributor to global GHGs emission. Therefore, the focus of this study is on solving a multi-period inventory routing problem (MIRP) involving carbon emission consideration based on carbon cap and offset policy. Hybrid genetic algorithm (HGA) based on allocation first and routing second is used to compute a solution for the MIRP in this study. The objective of this study is to solve the proposed MIRP model with HGA then validate the effectiveness of the proposed HGA on data of different sizes. Upon validation, the proposed MIRP model and HGA is applied on real-world data. The HGA is found to be able to solve small size and large size instances effectively by providing near optimal solution in relatively short CPU execution time.
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Ramkumar, N., P. Subramanian, T. T. Narendran, and K. Ganesh. "A hybrid heuristic for inventory routing problem." International Journal of Electronic Transport 1, no. 1 (2011): 45. http://dx.doi.org/10.1504/ijet.2011.043113.

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Bard, Jonathan F., and Narameth Nananukul. "The integrated production–inventory–distribution–routing problem." Journal of Scheduling 12, no. 3 (August 20, 2008): 257–80. http://dx.doi.org/10.1007/s10951-008-0081-9.

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Dissertations / Theses on the topic "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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Books on the topic "Inventory routing problem"

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Reiman, Martin I. Heavy traffic analysis of the dynamic stochastic inventory-routing problem. [Cambridge, Mass: Sloan School of Management, Massachusetts Institute of Technology], 1996.

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Book chapters on the topic "Inventory routing problem"

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Campbell, Ann, Lloyd Clarke, Anton Kleywegt, and Martin Savelsbergh. "The Inventory Routing Problem." In Fleet Management and Logistics, 95–113. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5755-5_4.

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Simić, Dragan, and Svetlana Simić. "Evolutionary Approach in Inventory Routing Problem." In Advances in Computational Intelligence, 395–403. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38682-4_42.

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Jiao, Yang, and R. Ravi. "Inventory Routing Problem with Facility Location." In Lecture Notes in Computer Science, 452–65. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24766-9_33.

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Malekly, Hooman. "The Inventory Pollution-Routing Problem Under Uncertainty." In Green Logistics and Transportation, 83–117. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17181-4_6.

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Al Shamsi, Ahmed, Ammar Al Raisi, and Muhammad Aftab. "Pollution-Inventory Routing Problem with Perishable Goods." In EcoProduction, 585–96. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07287-6_42.

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Alkawaleet, Nasir, Yi-Fang Hsieh, and Yanxiang Wang. "Inventory Routing Problem with CO2 Emissions Consideration." In EcoProduction, 611–19. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07287-6_44.

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Geiger, Martin Josef, and Marc Sevaux. "The Biobjective Inventory Routing Problem – Problem Solution and Decision Support." In Lecture Notes in Computer Science, 365–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21527-8_41.

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Touzout, Faycal A., Anne-Laure Ladier, and Khaled Hadj-Hamou. "Time-Dependent Travel-Time Constrained Inventory Routing Problem." In Lecture Notes in Computer Science, 151–66. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59747-4_10.

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Diniz, Pedro, Rafael Martinelli, and Marcus Poggi. "An Efficient Matheuristic for the Inventory Routing Problem." In Lecture Notes in Computer Science, 273–85. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53262-8_23.

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Yaşar Boz, Esra, Ahmet Reha Botsalı, and Tuba Ulusoy. "A New Approach to Location Routing Problem: Capacitated Periodic Location Routing Problem with Inventory." In Lecture Notes in Mechanical Engineering, 751–66. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62784-3_63.

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Conference papers on the topic "Inventory routing problem"

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Alves, Pedro Yuri A. L., Karina Valdivia Delgado, and Valdinei Freire da Silva. "Inventory Routing Problem with Time Windows." In the XIV Brazilian Symposium. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3229345.3229376.

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Cao, Jinxin, Jiachen Gao, Bing Li, and Xiangting Wang. "The Inventory Routing Problem: A Review." In 20th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2020. http://dx.doi.org/10.1061/9780784482933.385.

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Phuaksaman, Chayathach, and Patcharapong Penpakkol. "Heuristics for Multi-Depot Inventory Routing Problem." In 2019 Research, Invention, and Innovation Congress (RI2C). IEEE, 2019. http://dx.doi.org/10.1109/ri2c48728.2019.8999895.

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Moin, Noor Hasnah, and Huda Zuhrah Ab Halim. "Solving inventory routing problem with stochastic demand." In PROCEEDING OF THE 25TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM25): Mathematical Sciences as the Core of Intellectual Excellence. Author(s), 2018. http://dx.doi.org/10.1063/1.5041635.

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Zheng, Weibo, and Hong Zhou. "Robust Inventory Routing Problem with Replenishment Lead Time." In 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2019. http://dx.doi.org/10.1109/ieem44572.2019.8978718.

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Wong, Lily, and Noor Hasnah Moin. "Enhanced ant colony optimization for inventory routing problem." In THE 22ND NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM22): Strengthening Research and Collaboration of Mathematical Sciences in Malaysia. AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4932470.

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Ghani, Nor Edayu Abd, S. Sarifah Radiah Shariff, and Siti Meriam Zahari. "Optimization of location routing inventory problem with transshipment." In INTERNATIONAL CONFERENCE ON MATHEMATICS, ENGINEERING AND INDUSTRIAL APPLICATIONS 2014 (ICoMEIA 2014). AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4915676.

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Zhenping Li, Lulu Jiang, and Chongyu Jiang. "An inventory routing problem with soft time windows." In 12th International Symposium on Operations Research and its Applications in Engineering, Technology and Management (ISORA 2015). Institution of Engineering and Technology, 2015. http://dx.doi.org/10.1049/cp.2015.0614.

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Kawamura, T., T. Sato, and T. Shiina. "Multi-product Inventory Routing Problem Considering Demand Uncertainty." In 2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2022. http://dx.doi.org/10.1109/iiaiaai55812.2022.00123.

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Xie Binglei, An Shi, and Wang Jian. "Stochastic inventory routing problem under B2C e-commerce." In IEEE International Conference on e-Business Engineering (ICEBE'05). IEEE, 2005. http://dx.doi.org/10.1109/icebe.2005.112.

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Reports on the topic "Inventory routing problem"

1

COLUMBIA UNIV NEW YORK. Analytical Analysis of Vehicle Routing and Inventory Routing Problems. Fort Belvoir, VA: Defense Technical Information Center, December 1998. http://dx.doi.org/10.21236/ada358629.

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