Relevant bibliographies by topics / Vehicle routing problem with loading constraints

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Academic literature on the topic 'Vehicle routing problem with loading constraints'

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Published: 10 January 2023
Last updated: 28 January 2023

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Journal articles on the topic "Vehicle routing problem with loading constraints"

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Ostermeier, Manuel, Sara Martins, Pedro Amorim, and Alexander Hübner. "Loading constraints for a multi-compartment vehicle routing problem." OR Spectrum 40, no. 4 (June 29, 2018): 997–1027. http://dx.doi.org/10.1007/s00291-018-0524-4.

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Yi, Junmin, Zhixiong Su, and Yihui Qiu. "The vehicle routing problem with one-dimensional loading constraints." International Journal of Industrial and Systems Engineering 27, no. 3 (2017): 412. http://dx.doi.org/10.1504/ijise.2017.087193.

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Qiu, Yihui, Junmin Yi, and Zhixiong Su. "The vehicle routing problem with one-dimensional loading constraints." International Journal of Industrial and Systems Engineering 27, no. 3 (2017): 412. http://dx.doi.org/10.1504/ijise.2017.10007560.

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Doerner, Karl F., Guenther Fuellerer, Richard F. Hartl, Manfred Gronalt, and Manuel Iori. "Metaheuristics for the vehicle routing problem with loading constraints." Networks 49, no. 4 (2007): 294–307. http://dx.doi.org/10.1002/net.20179.

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Chen, Zongyi, Mingkang Yang, Yijun Guo, Yu Liang, Yifan Ding, and Li Wang. "The Split Delivery Vehicle Routing Problem with Three-Dimensional Loading and Time Windows Constraints." Sustainability 12, no. 17 (August 27, 2020): 6987. http://dx.doi.org/10.3390/su12176987.

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Besides routing and packing plans, synthetically considering the requirements of customers about service time is absolutely necessary. An order split delivery plan can not only better satisfy the service time requirements, but also improve the full-load rate of vehicles. The split delivery vehicle routing problem with three-dimensional loading constraints (3L-SDVRP) combines vehicle routing and three-dimensional loading with additional packing constraints. In the 3L-SDVRP splitting deliveries of customers is basically possible, i.e., a customer can be visited in two or more tours. The vehicle routing problem with three-dimensional loading constraints that are based on the time window and considering split delivery of orders (3L-CVRPTWSDO) and its optimization algorithm are studied in this paper. We established mathematical model of the problem and designed the tabu search algorithm. Based on the examples used in Gendreau et al. (2006), examples was constructed to test our algorithm. The experimental results have expressed that, in the 3L-CVRP problem, the results of split delivery is better than those of non-split delivery, and it is easier to satisfy the time window constraints. The algorithm in this paper generates high quality solutions, it provides a effective method to solve the 3L-CVRPTWSDO problems.
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Candido, Lilian Caroline Xavier, and Luzia Vidal de Souza. "Mathematical Model and Simulated Annealing Algorithm for the Two-Dimensional Loading Heterogeneous Fixed Fleet Vehicle Routing Problem." Mathematical Problems in Engineering 2022 (January 28, 2022): 1–19. http://dx.doi.org/10.1155/2022/6012105.

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This paper addresses the two-dimensional loading heterogeneous fixed fleet vehicle routing problem, which is a complex and unstudied variant of the classical vehicle routing problem and has a wide range of applications in transportation and logistics fields. In this problem, each customer demands a set of rectangular two-dimensional items, and the objective is to find the minimum cost delivery routes for a limited set of vehicles with different capacities, fixed and variable operating costs, and rectangular two-dimensional loading surfaces. We formulate a mixed integer linear programming model to obtain optimal solutions for small-scale problems. To obtain solutions for large-scale problems, we develop an algorithm based on simulated annealing and local search, which uses a collection of packing heuristics to address the loading constraints, and we also propose three new heuristics. We conduct experiments on benchmark instances derived from the two-dimensional loading heterogeneous fleet vehicle routing problem. The results indicate that the proposed model correctly describes the problem and can solve small-scale problems, that the new packing heuristics are effective in improving the collection of packing heuristics, and that the proposed simulated annealing algorithm can find good solutions to large-scale problems within an acceptable computational time. Hence, it can be used by logistic companies using a heterogeneous fixed fleet in the integrated planning of vehicle loading and routing.
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Meliani, Youssef, Yasmina Hani, Sâad Lissane Elhaq, and Abderrahman El Mhamedi. "Vehicle routing problem with three-dimensional loading constraints: Experimentations and evaluation." IFAC-PapersOnLine 54, no. 1 (2021): 104–9. http://dx.doi.org/10.1016/j.ifacol.2021.08.076.

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Bortfeldt, Andreas, and Junmin Yi. "The Split Delivery Vehicle Routing Problem with three-dimensional loading constraints." European Journal of Operational Research 282, no. 2 (April 2020): 545–58. http://dx.doi.org/10.1016/j.ejor.2019.09.024.

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Zhang, Qun, Li Rong Wei, Rui Hu, Rui Yan, Li Hua Li, and Xiao Ning Zhu. "A Review on the Bin Packing Capacitated Vehicle Routing Problem." Advanced Materials Research 853 (December 2013): 668–73. http://dx.doi.org/10.4028/www.scientific.net/amr.853.668.

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This paper introduced the Bin Packing Capacitated Vehicle Routing Problem. It introduced the constraints and differences between algorithms of two-dimensional and three-dimensional loading capacitated vehicle routing problem. It gave a review of models and algorithms for Bin Packing Capacitated VRP. Finally, it prospected future research orientations and possible improvement in this area.
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Dabia, Said, Stefan Ropke, and Tom van Woensel. "Cover Inequalities for a Vehicle Routing Problem with Time Windows and Shifts." Transportation Science 53, no. 5 (September 2019): 1354–71. http://dx.doi.org/10.1287/trsc.2018.0885.

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This paper introduces the vehicle routing problem with time windows and shifts (VRPTWS). At the depot, several shifts with nonoverlapping operating periods are available to load the planned trucks. Each shift has a limited loading capacity. We solve the VRPTWS exactly by a branch-and-cut-and-price algorithm. The master problem is a set partitioning with an additional constraint for every shift. Each constraint requires the total quantity loaded in a shift to be less than its loading capacity. For every shift, a pricing subproblem is solved by a label-setting algorithm. Shift capacity constraints define knapsack inequalities; hence we use valid inequalities inspired from knapsack inequalities to strengthen the linear programming relaxation of the master problem when solved by column generation. In particular, we use a family of tailored robust cover inequalities and a family of new nonrobust cover inequalities. Numerical results show that nonrobust cover inequalities significantly improve the algorithm.
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Dissertations / Theses on the topic "Vehicle routing problem with loading constraints"

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Koch, Henriette [Verfasser]. "Vehicle routing problems with three-dimensional loading constraints and backhauls / Henriette Koch." Magdeburg : Universitätsbibliothek, 2018. http://d-nb.info/1167856570/34.

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Santini, Luigi Tavolaro. "Meta-heurísticas para problemas integrados de roteamento e carregamento de veículos." Universidade Nove de Julho, 2017. http://bibliotecatede.uninove.br/handle/tede/1727.

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The present work deals with the Capacitated Vehicle Routing Problem with Three-Dimensional Loading Constraints. This problem is difficult to solve exactly, still relatively little studied, but important in the logistics activities of movement, warehousing and transportation. This problem consists in minimizing the total traveled distance by a homogeneous fleet of vehicles that address the issue of deliveries of customer demands, in which these demands are composed of items that have three relevant spatial dimensions. The objective of the present work is to develop heuristic and metaheuristic algorithms to solve the problem in question. The algorithms are based on the Clarke & Wright and George & Robinson heuristics, and on the Iterated Local Search and Adaptive Large Neighborhood Search metaheuristics. In the proposed algorithm, the routing problem is firstly addressed by adapting the Clarke & Wright heuristic, creating routes that are used to verify the loading pattern, thus obtaining an initial solution. In the following, an extensive search in the solution neighborhood is applied with the Iterated Local Search metaheuristic. For the best results of this search, it is checked if the loading pattern is feasible using an adapted George & Robinson algorithm. If it is not feasible, the Adaptive Large Neighborhood Search metaheuristic is executed in an attempt to find a feasible solution to the loading problem. Instances from the literature are used to evaluate the efficiency of the developed methods. The results obtained for the routing problem individually were of paramount importance to ensure the effectiveness of the Iterated Local Search metaheuristic. For the loading problem individually, the tests were also satisfactory, allowing for several feasible loading patterns using the adapted George & Robinson algorithm and the Adaptive Large Neighborhood Search metaheuristic. The results obtained with the proposed algorithm for the integrated problem were also good, being very close to those in the literature and with computational time relatively lower. As perspectives for future research, it is intended to investigate more efficient ways of exploring the solution space of the integrated problem, as well as the use of other metaheuristics.
O presente trabalho trata do Problema de Roteamento de Veículos Capacitado com Restrições de Carregamento Tridimensional. Este é um problema de difícil solução exata, ainda relativamente pouco estudado, porém importante nas atividades logísticas de movimentação, armazenagem e transporte de produtos. Este problema consiste em minimizar a distância total percorrida por uma frota homogênea de veículos que supram a questão das entregas das demandas de clientes, em que tais demandas são compostas por itens que possuem três dimensões espaciais relevantes. O objetivo do presente trabalho consiste em desenvolver algoritmos heurísticos e meta-heurísticos para resolver o problema em questão. Os algoritmos são baseados nas heurísticas de Clarke & Wright e de George & Robinson, e nas meta-heurísticas Iterated Local Search e Adaptive Large Neighborhood Search. No algoritmo proposto, primeiro trata-se o problema de roteamento adaptando-se a heurística de Clarke & Wright, criando roteiros que são utilizados para a verificação do padrão de carregamento, tendo-se assim uma solução inicial. Em seguida, é aplicada uma busca extensiva na vizinhança com a meta-heurística Iterated Local Search. Para os melhores resultados desta busca, verifica-se se o padrão de carregamento é viável utilizando o algoritmo de George & Robinson adaptado. Nos casos em que não é viável, a meta-heurística Adaptive Large Neighborhood Search é executada na tentativa de se encontrar soluções viáveis para o problema de carregamento. Instâncias da literatura são utilizadas para avaliar a eficiência dos métodos desenvolvidos. Os resultados obtidos para o problema de roteamento separadamente foram de suma importância para assegurar a eficiência do meta-heurística Iterated Local Search. Para o problema de carregamento separadamente, os testes utilizando o algoritmo de George & Robinson adaptado e a meta-heurística Adaptive Large Neighborhood Search também foram satisfatórios, permitindo a obtenção de vários padrões de carregamento factíveis. Os resultados obtidos com o algoritmo proposto para o problema integrado também foram bons, sendo bastante próximos aos da literatura e com tempo computacional relativamente menor. Como perspectivas de pesquisas futuras, pretende-se estudar formas mais eficientes de se explorar o espaço de busca do problema integrado, bem como a utilização de outras meta-heurísticas.
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Ferreira, Kamyla Maria. "Proposta de um framework para problemas que integram decisões de localização, roteamento e empacotamento." Universidade Federal de Goiás, 2018. http://repositorio.bc.ufg.br/tede/handle/tede/8209.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
This research deals with the resolution of problems that involve the location, routing, and packing decisions with focus on the location routing problem, capacitated vehicle routing problem with two-dimensional loading constraints, and location routing problem with two-dimensional loading constraints. For that, it is proposed a framework that reuses part of the algorithms, which are of a common domain, such that the development of the project is systematized. The objective of the framework is allowing the resolution of different variants of problems that integrate location, routing, and packing decisions without the need to replicate algorithms. As a proposal for an algorithm, it is developed a hybrid heuristic, which involves the cooperation between the simulated annealing and the artificial algae algorithm. The simulated annealing has four neighborhood operators, local search, and three procedures to diversify the solution. The artificial algae algorithm is combined with the skyline method in order to verify the feasibility of the two-dimensional packing constraints. Once the framework and heuristics have been codified, computational experiments are performed to test its performance, as well as comparisons are made with the most recent results published in the literature. The results show that the heuristic is competitive with other methods from the literature since it could obtain 36.25% solutions equal to the best ones reported in the literature of the location routing problem, besides the average GAP being 0.57%. For the vehicle routing problem with two-dimensional loading constraints, the heuristic could obtain 43.05% solutions equal to the best known in the literature, besides the average GAP being 3.33%. The results obtained for the location routing problem with twodimensional loading constraints were satisfactory.
Este trabalho trata da resolução de problemas que envolvem decisões de localização, roteamento e empacotamento com foco nos problemas de localização e roteamento, roteamento de veículos capacitado com restrições de empacotamento bidimensional, e localização e roteamento com restrições de empacotamento bidimensional. Para tanto, propõe-se um framework capaz de reutilizar parte dos algoritmos, que são de domínio comum, para que o desenvolvimento do projeto seja sistematizado. O objetivo é que o framework possibilite a resolução de diferentes variantes do problema que integram as decisões de localização, roteamento e empacotamento sem ter que replicar algoritmos. Como proposta de algoritmo, desenvolve-se uma heurística híbrida, a qual envolve a cooperação entre dois métodos, o recozimento simulado e o algoritmo artificial de algas. O recozimento simulado possui quatro operadores de vizinhança, procedimentos de busca local e três procedimentos para diversificar a solução. O algoritmo artificial de algas é combinado com a técnica Skyline para verificar as restrições de empacotamento bidimensional. A partir da codificação do framework e da heurística, experimentos computacionais foram realizados para testar o seu desempenho e comparar os resultados com os mais recentes da literatura. Os resultados indicam que a heurística é competitiva com os demais métodos da literatura, sendo possível obter 36,25% de soluções iguais às melhores reportadas na literatura do problema de localização e roteamento, além do GAP médio ter sido de 0,57%. No problema de roteamento de veículos com restrições de empacotamento bidimensional, a heurística obteve 43,05% soluções iguais às melhores conhecidas na literatura, além do GAP médio ter sido de 3,33%. Os resultados obtidos para o problema de localização e roteamento com restrições de empacotamento bidimensional foram satisfatórios.
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Johar, Farhana. "Vehicle routing problem with availability constraints." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/389516/.

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This work is concerned with solving the vehicle routing problem (VRP) which takes into account the customer's release and due date. The problem studied can also be categorized as a non-classical VRP as the departure times of vehicles depend on the dates of orders released from the production line and become available for the distribution process. Hence, the problem is known as VRP with availability constraints (VRPAC). The VRPAC is investigated through two stages. In the first stage, vehicle routing problem with release and due date (VRPRDD) is treated. At the beginning of the planning, it is assumed that the dates where the customer orders become available are known. A mathematical formulation is developed to represent the problem studied which has been solved by several heuristics, i.e. Variable Neighborhood Search (VNS), Large Neighborhood Search (LNS) and Tabu Search (TS). The algorithms are written in C++ and run on a PC computer with an Intel PentiumCore by using 56's Solomon instances with some modification. Different kinds of vehicle routing problem has been tackled in order to see the performance of proposed heuristics. The results are then compared in order to find the best method which yields the least routing cost solution. From the outcome obtained, VNS is proved to be the best algorithm which generates the least cost solution to our problem. Further investigation has been carried out in stage two which considers the extension of VRPRDD. The coordination of production sequence and vehicle routing (PS-VRPRDD) is the main subject to our problem studied in which the best production sequence will leads to the least routing. Two proposed algorithms have been used to run the test instances. The first is classical decomposition approach; Alternate which decompose the problems into two sub-problems, i.e. production sequence and vehicle routing. This will be used as benchmark to the second approach; InOneMove which take these two decisions of the sub-problems as a whole. Decision on both sub-problems is considered simultaneously as one move. The results proved that effective coordination shows the large potential savings that attract the interest of industrial distributors in optimizing their distribution process in practice.
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Yahiaoui, Ala-Eddine. "Selective vehicle routing problem : cluster and synchronization constraints." Thesis, Compiègne, 2018. http://www.theses.fr/2018COMP2449/document.

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Le problème de tournées de véhicules (Vehicle Routing Problem - VRP) est un problème d'optimisation combinatoire utilisé généralement pour modéliser et résoudre des différents problèmes rencontrés dans les systèmes logistiques et de transport. Dans cette thèse, nous nous sommes intéressés à l'étude et la résolution d'une classe de problèmes du VRP appelée les problèmes de courses d'orientation (Team Orienteering Problem - TOP). Dans cette catégorie de problèmes, il est a priori impossible de visiter tous les clients en raison de ressources limitées. On associe plutôt un profit à chaque client qui représente sa valeur. Ce profit est collecté lorsque le client est visité par l'un des véhicules disponibles. L'objectif est donc de sélectionner un sous ensemble de clients à servir tout en maximisant le profit total collecté. Dans un premier temps, nous avons introduit une nouvelle généralisation pour le TOP que nous avons appelé le Clustered TOP ou CluTOP. Dans cette variante, les clients sont regroupés en sous-ensembles appelés clusters auxquels nous associons des profits. Pour résoudre cette variante, nous avons proposé un schéma exact basé sur l'approche des plans sécants avec des inégalités valides supplémentaires et des pré-traitements. Nous avons également conçu une méthode heuristique basée sur l'approche order first-cluster second. Cette heuristique hybride combine une heuristique de type Adaptive Large Neighborhood Search qui explore l'espace des solutions et une procédure de découpage qui explore l'espace de recherche des tours géants. De plus, la procédure de découpage est renforcée par une recherche locale afin de mieux explorer l'espace de recherche. Le deuxième problème traité dans ce travail s'appelle le Synchronized Team Orienteering Problem with Time Windows (STOPTW). Cette variante avait été initialement proposée afin de modéliser des scénarios liés à la protection des infrastructures stratégiques menacées par l'avancée des feux de forêts. En plus des contraintes de fenêtres de temps et des visites synchronisées, cette variante considère le cas d'une flotte de véhicules hétérogène. Pour résoudre ce problème, nous avons proposé une méthode heuristique basée sur l'approche GRASP×ILS qui est parvenue à dominer la seule approche existante dans la littérature. La dernière variante du TOP abordée dans cette thèse s'appelle le Set Orienteering Problem (SOP). Les clients dans cette variante sont regroupés en sous-ensembles appelés clusters. Un profit est associé à chaque groupe qui n'est obtenu que si au moins un client est desservi par le véhicule disponible. Nous avons proposé une méthode de coupes avec deux procédures de séparation pour séparer les contraintes d'élimination des sous-tours. Nous avons également proposé un algorithme Mémétique avec une procédure de découpage optimale calculée à l'aide de la programmation dynamique
The Vehicle Routing Problem (VRP) is a family of Combinatorial Optimization Problems generally used to solve different issues related to transportation systems and logistics. In this thesis, we focused our attention on a variant of the VRP called the Team Orienteering Problem (TOP). In this family of problems, it is a priory impossible to visit all the customers due to travel time limitation on vehicles. Instead, a profit is associated with each customer to represent its value and it is collected once the customer is visited by one of the available vehicles. The objective function is then to maximize the total collected profit with respect to the maximum travel time. Firstly, we introduced a new generalization for the TOP that we called the Clustered TOP (CluTOP). In this variant, the customers are grouped into subsets called clusters to which we associate profits. To solve this variant, we proposed an exact scheme based on the cutting plane approach with additional valid inequalities and pre-processing techniques. We also designed a heuristic method based on the order first-cluster second approach for the CluTOP. This Hybrid Heuristic combines between an ANLS heuristic that explores the solutions space and a splitting procedure that explores the giant tours search space. In addition, the splitting procedure is enhanced by local search procedure in order to enhance its coverage of search space. The second problem treated in this work is called the Synchronized Team Orienteering Problem with Time Windows (STOPTW). This variant was initially proposed in order to model scenarios related to asset protection during escaped wildfires. It considers the case of a heterogeneous fleet of vehicles along with time windows and synchronized visits. To solve this problem, we proposed a heuristic method based on the GRASP×ILS approach that led to a very outstanding results compared to the literature. The last variant of the TOP tackled in this thesis called the Set Orienteering Problem (SOP). Customers in this variant are grouped into subsets called clusters. Each cluster is associated with a profit which is gained if at least one customer is served by the single available vehicle. We proposed a Branch-and-Cut with two separation procedures to separate subtours elimination constraints. We also proposed a Memetic Algorithm with an optimal splitting procedure based on dynamic programming
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Parolin, Erick Skorupa. "Asynchronous teams for solving the loading and routing auto-carrier problem." reponame:Repositório Institucional da UFABC, 2016.

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Orientador: Prof. Dr. Cláudio Nogueira de Meneses
Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Ciência da Computação, 2016.
Beyond a complex real world system composed by a set of sophisticated machines and qualied human resources distributed around manufacturing environment, the Auto In- dustry needs a little more to allow their products to reach the nal costumers. Loading vehicles like cars, trucks and vans into auto-carriers and designing routes to delivery sub- sets of vehicles to auto dealers according to their orders are relevant tasks in automotive value chain performed by transportation companies. Given the set of complex constraints related to diferent vehicle models (with diferent dimensions) to be feasibly loaded into dierent auto-carrier models plus the auto-carrier eet routing task, transportation com- panies must explore strong computational alternatives to address this optimization prob- lem. In fact, we explore in this dissertation a real world complex problem composed by two sub-problems, both belonging to NP-hard class: routing and loading. After formally dening the tackled problem, we adopt, in this dissertation, a previously studied procedure based on enumeration techniques for loading task and we propose an alternative approach employing Asynchronous Teams concept, which combines local search algorithms in order to cooperate to each other to try to resolve the routing sub-problem. Setting the results provided by our implementation of Iterated Local Search (ILS) approach (already proposed in literature for solving the routing sub-problem) as benchmark, we propose computational experiments considering real-world instances, to compare performance of ILS to ve vari- ants of our Asynchronous Teams implementations. Final results evidence the power of this proposed alternative approach for founding quality solutions and its exibility to easily assume diferent configurations.
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Kocak, Menekse. "Vehicle Routing Problem In Cross Dockswith Shift-based Time Constraints On Products." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613945/index.pdf.

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In this study, the capacitated vehicle routing problem with shift based time constraints is taken into consideration. The study stemmed from an application in a cross dock. The considered cross dock is assumed to feed directly the production lines of its customer. The customer has a just-in-time production system that requires producing only in necessary quantities at the necessary times. This necessitates the arrival of the parts/products collected from different suppliers at the customer at the beginning of each shift of production. The shift times constitute deadlines for the products to be collected from the suppliers and used in each shift. The collection problem then can be seen as the capacitated vehicle routing problem with shift based time constraints. The objective of the collection problem is to minimize the routing costs. For the accomplishment of this objective it is required to decide on products of which shift(s) should be taken from a supplier when a vehicle arrives at that supplier. For the solution of the problem a mathematical model is formulated. Since the dealt problem is NP-Hard, meta-heuristic solution approaches based on variable neighborhood search and simulated annealing are proposed. Computational experimentation is conducted on the test problems which are tailored from the capacitated vehicle routing instances from the literature.
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El-Nashar, Ahmed. "Multi-Vehicle Dispatching and Routing with Time Window Constraints and Limited Dock Capacity." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5197.

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The Vehicle Routing Problem with Time Windows (VRPTW) is an important and computationally hard optimization problem frequently encountered in Scheduling and logistics. The Vehicle Routing Problem (VRP) can be described as the problem of designing the most efficient and economical routes from one depot to a set of customers using a limited number of vehicles. This research addresses the VRPTW under the following additional complicating features that are often encountered in practical problems: 1. Customers have strict time windows for receiving a vehicle, i.e., vehicles are not allowed to arrive at the customer's location earlier than the lower limit of the specified time window, which is relaxed in previous research work. 2. There is a limited number of loading/unloading docks for dispatching/receiving the vehicles at the depot The main goal of this research is to propose a framework for solving the VRPTW with the constraints stated above by generating near-optimal routes for the vehicles so as to minimize the total traveling distance. First, the proposed framework clusters customers into groups based on their proximity to each other. Second, a Probabilistic Route Generation (PRG) algorithm is applied to each cluster to find the best route for visiting customers by each vehicle; multiple routes per vehicle are generated and each route is associated with a set of feasible dispatching times from the depot. Third, an assignment problem formulation determines the best dispatching time and route for each vehicle that minimizes the total traveling distance. iii The proposed algorithm is tested on a set of benchmark problems that were originally developed by Marius M. Solomon and the results indicate that the algorithm works well with about 1.14% average deviation from the best-known solutions. The benchmark problems are then modified by adjusting some of the customer time window limits, and adding the staggered vehicle dispatching constraint. For demonstration purposes, the proposed clustering and PRG algorithms are then applied to the modified benchmark problems.
Ph.D.
Doctorate
Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering
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Kent, Edward. "The effects of synchronisation and other forestry commissioning constraints on vehicle routing problem solution methods." Thesis, University of Nottingham, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.716670.

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Urbanovsky, Joshua C. "Computational Methods to Optimize High-Consequence Variants of the Vehicle Routing Problem for Relief Networks in Humanitarian Logistics." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1248473/.

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Optimization of relief networks in humanitarian logistics often exemplifies the need for solutions that are feasible given a hard constraint on time. For instance, the distribution of medical countermeasures immediately following a biological disaster event must be completed within a short time-frame. When these supplies are not distributed within the maximum time allowed, the severity of the disaster is quickly exacerbated. Therefore emergency response plans that fail to facilitate the transportation of these supplies in the time allowed are simply not acceptable. As a result, all optimization solutions that fail to satisfy this criterion would be deemed infeasible. This creates a conflict with the priority optimization objective in most variants of the generic vehicle routing problem (VRP). Instead of efficiently maximizing usage of vehicle resources available to construct a feasible solution, these variants ordinarily prioritize the construction of a minimum cost set of vehicle routes. Research presented in this dissertation focuses on the design and analysis of efficient computational methods for optimizing high-consequence variants of the VRP for relief networks. The conflict between prioritizing the minimization of the number of vehicles required or the minimization of total travel time is demonstrated. The optimization of the time and capacity constraints in the context of minimizing the required vehicles are independently examined. An efficient meta-heuristic algorithm based on a continuous spatial partitioning scheme is presented for constructing a minimized set of vehicle routes in practical instances of the VRP that include critically high-cost penalties. Multiple optimization priority strategies that extend this algorithm are examined and compared in a large-scale bio-emergency case study. The algorithms designed from this research are implemented and integrated into an existing computational framework that is currently used by public health officials. These computational tools enhance an emergency response planner's ability to derive a set of vehicle routes specifically optimized for the delivery of resources to dispensing facilities in the event of a bio-emergency.
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Book chapters on the topic "Vehicle routing problem with loading constraints"

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Krebs, Corinna, and Jan Fabian Ehmke. "Vertical Stability Constraints in Combined Vehicle Routing and 3D Container Loading Problems." In Lecture Notes in Computer Science, 442–55. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87672-2_29.

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Pinto, Telmo, Cláudio Alves, and José Valério de Carvalho. "A Branch-and-Price Algorithm for the Vehicle Routing Problem with 2-Dimensional Loading Constraints." In Lecture Notes in Computer Science, 321–36. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44896-1_21.

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Sassi Mahfoudh, Soumaya, and Monia Bellalouna. "A Hybrid Heuristic for the Probabilistic Capacitated Vehicle Routing Problem with Two-Dimensional Loading Constraints." In Lecture Notes in Computer Science, 241–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93713-7_20.

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Yi, Junmin, and Andreas Bortfeldt. "The Capacitated Vehicle Routing Problem with Three-Dimensional Loading Constraints and Split Delivery—A Case Study." In Operations Research Proceedings 2016, 351–56. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55702-1_47.

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Mak-Hau, Vicky, I. Moser, and Aldeida Aleti. "An Exact Algorithm for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints." In Lecture Notes in Management and Industrial Engineering, 91–101. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55914-8_7.

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Huang, Min-fang, and Yuan-kai Zhang. "A Solution Procedure for the Capacitated Vehicle Routing Problem with Three-Dimensional Loading Constraints in Online Supermarket Delivery." In The 19th International Conference on Industrial Engineering and Engineering Management, 1159–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38427-1_122.

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Turky, Ayad, I. Moser, and Aldeida Aleti. "An Iterated Local Search with Guided Perturbation for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints." In Lecture Notes in Computer Science, 279–90. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-51691-2_24.

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Yu, Miao, Viswanath Nagarajan, and Siqian Shen. "Minimum Makespan Vehicle Routing Problem with Compatibility Constraints." In Integration of AI and OR Techniques in Constraint Programming, 244–53. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59776-8_20.

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Sarasola, Briseida, and Karl F. Doerner. "Solving a Multi-objective Vehicle Routing Problem with Synchronization Constraints." In Lecture Notes in Computer Science, 532–46. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87672-2_35.

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de Queiroz, Thiago Alves, José Fernando Oliveira, Maria Antónia Carravilla, and Flávio Keidi Miyazawa. "Demand Uncertainty for the Location-Routing Problem with Two-dimensional Loading Constraints." In Lecture Notes in Economics and Mathematical Systems, 47–53. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-20430-7_7.

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Conference papers on the topic "Vehicle routing problem with loading constraints"

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Wang, Fan, Yi Tao, and Ning Shi. "A Survey on Vehicle Routing Problem with Loading Constraints." In 2009 International Joint Conference on Computational Sciences and Optimization, CSO. IEEE, 2009. http://dx.doi.org/10.1109/cso.2009.127.

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Wang, Qing, Shuai Peng, and Min Huang. "The hybrid vehicle routing problem with backhauls and 3D loading constraints." In 2021 33rd Chinese Control and Decision Conference (CCDC). IEEE, 2021. http://dx.doi.org/10.1109/ccdc52312.2021.9601523.

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Annouch, Anouar, Adil Bellabdaoui, and Jawad Minkhar. "Split delivery and pickup vehicle routing problem with two-dimensional loading constraints." In 2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA). IEEE, 2016. http://dx.doi.org/10.1109/sita.2016.7772277.

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Li, Jian, and Lin Li. "Vehicle Routing Problem of Simultaneous Deliveries and Pickups with Two-Dimensional Loading Constraints." In Fourth International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2013. http://dx.doi.org/10.1061/9780784413159.386.

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Abdal-Hammed, Moudher Kh, Mhand Hifi, and Lei Wu. "Large neighborhood search for the vehicle routing problem with two-dimensional loading constraints." In 2014 International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2014. http://dx.doi.org/10.1109/codit.2014.6996867.

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Escobar, Luis Miguel, David Alvarez Martinez, John Willmer Escobar, Rodrigo Linfati, and Granada E. Mauricio. "A hybrid metaheuristic approach for the capacitated vehicle routing problem with container loading constraints." In 2015 International Conference on Industrial Engineering and Systems Management (IESM). IEEE, 2015. http://dx.doi.org/10.1109/iesm.2015.7380331.

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Yi Tao and Fan Wang. "A new packing heuristic based algorithm for Vehicle Routing Problem with Three-dimensional Loading constraints." In 2010 IEEE International Conference on Automation Science and Engineering (CASE 2010). IEEE, 2010. http://dx.doi.org/10.1109/coase.2010.5584159.

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Sbai, Ines, and Saoussen Krichen. "An Adaptive Genetic Algorithm for Dynamic Vehicle Routing Problem with Backhaul and Two-dimensional loading constraints." In 2020 International Multi-Conference on: “Organization of Knowledge and Advanced Technologies” (OCTA). IEEE, 2020. http://dx.doi.org/10.1109/octa49274.2020.9151691.

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Sun, HaiFeng, KaiTai Dong, Qun Zhang, and Rui Yan. "An improved particle swarm algorithm for heterogeneous fleet vehicle routing problem with two-dimensional loading constraints." In International Conference on Materials Engineering and Information Technology Applications (MEITA 2015). Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/meita-15.2015.74.

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Peng, Bitao. "Hybrid Tabu Search Algorithm for Fleet Size and Mixed Vehicle Routing Problem with Three-Dimensional Loading Constraints." In 2018 11th International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2018. http://dx.doi.org/10.1109/iscid.2018.00073.

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Reports on the topic "Vehicle routing problem with loading constraints"

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She, Ruifeng, and Yanfeng Ouyang. Generalized Link-Cost Function and Network Design for Dedicated Truck-Platoon Lanes to Improve Energy, Pavement Sustainability, and Traffic Efficiency. Illinois Center for Transportation, November 2021. http://dx.doi.org/10.36501/0197-9191/21-037.

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Recent development of autonomous and connected trucks (ACT) has provided the freight industry with the option of using truck platooning to improve fuel efficiency, traffic throughput, and safety. However, closely spaced and longitudinally aligned trucks impose frequent and concentrated loading on pavements, which often accelerates pavement deterioration and increases the life cycle costs for the highway agency. Also, effectiveness of truck platooning can be maximized only in dedicated lanes; and its benefits and costs need to be properly balanced between stakeholders. This paper proposes a network-design model to optimize (i) placement of dedicated truck-platoon lanes and toll price in a highway network, (ii) pooling and routing of ACT traffic from multiple origins and destinations to utilize these lanes, and (iii) configuration of truck platoons within these lanes (e.g., lateral displacements and vehicle separations). The problem is formulated as an integrated bi-level optimization model. The upper level makes decisions on converting existing highway lanes into dedicated platoon lanes, as well as setting user fees. The lower-level decisions are made by independent shippers regarding the choice of routes and use of platoon lanes vs. regular lanes; and they collectively determine truck traffic in all lanes. Link-cost functions for platoon lanes are obtained by simultaneously optimizing, through dynamic programming, pavement-rehabilitation activities and platoon configuration in the pavement's life cycle. A numerical case study is used to demonstrate the applicability and performance of the proposed model framework over the Illinois freeway system. It is shown that the freight traffic is effectively channelized on a few corridors of platoon lanes and, by setting proper user fees to cover pavement-rehabilitation costs, systemwide improvements for both freight shippers and highway agencies can be achieved.
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