Many-to-many location-routing with inter-hub transport and multi-commodity pickup-and-delivery

Rieck, Julia; Ehrenberg, Carsten; Zimmermann, Jürgen

doi:10.1016/j.ejor.2013.12.021

Cited by 83 publications

(32 citation statements)

References 42 publications

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“…Yaman and Elloumi [75] also considered a star hub network, while Contreras et al [15] investigated a tree structure. Rieck et al [64] investigated a variant found in the timber-trade industry that considers a general hub network where hubs are limited to a set of potential locations, in which pickup and delivery are not necessarily simultaneous, and where non-hub nodes are categorized as supply and delivery points. Their mixed-integer programming formulation, strengthened with general and instance dependent inequalities, solved instances to optimality whose total number of nodes were at most 17.…”

Section: Literature Review Of the Mmlrpmentioning

confidence: 99%

Heuristics for a hub location‐routing problem

Lopes

Andrade²,

Queiroz

et al. 2016

Networks

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We investigate a variant of the many‐to‐many hub location‐routing problem which consists in partitioning the set of nodes of a graph into routes containing exactly one hub each, and determining an extra route interconnecting all hubs. A variable neighborhood descent with neighborhood structures based on remove/add, swap and exchange moves nested with routing and location operations is used as a local search procedure in a multistart algorithm. We also consider a sequential version of this local search in the multistart. In addition, a biased random‐key genetic algorithm working with a local search routine, which also considers routing and location operations, is applied to the problem. To compare the heuristic solutions, we develop an integer programming formulation which is solved with a branch‐and‐cut algorithm. Capacity and path elimination constraints are added in a cutting plane fashion. The separation algorithms are based on the computation of min‐cut trees and on the connected components of a support graph. Computational experiments were conducted on several benchmark instances of routing problems and show that the heuristics are effective on medium to large‐sized instances, while the branch‐and‐cut algorithm solves small to medium sized problems to optimality. These algorithms were also compared with a commercial hybrid solver showing that the heuristics are quite competitive. © 2016 Wiley Periodicals, Inc. NETWORKS, Vol. 68(1), 54–90 2016

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Section: Literature Review Of the Mmlrpmentioning

confidence: 99%

Heuristics for a hub location‐routing problem

Lopes

Andrade²,

Queiroz

et al. 2016

Networks

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“…We summarize the different features of the related studies in Table 1. Some other variants of hub location and routing problems have been addressed by Aykin [5], Catanzaro et al [17], and Rieck et al [42].…”

Section: Introductionmentioning

confidence: 99%

A branch-and-cut algorithm for the hub location and routing problem

Rodríguez-Martín

Salazar-González

Yaman

2014

Computers & Operations Research

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We study the hub location and routing problem where we decide on the location of hubs, the allocation of nodes to hubs, and the routing among the nodes allocated to the same hubs, with the aim of minimizing the total transportation cost. Each hub has one vehicle that visits all the nodes assigned to it on a cycle. We propose a mixed integer programming formulation for this problem and strengthen it with valid inequalities. We devise separation routines for these inequalities and develop a branch-and-cut algorithm which is tested on CAB and AP instances from the literature. The results show that the formulation is strong and the branch-and-cut algorithm is able to solve instances with up to 50 nodes. © 2014 Elsevier Ltd

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“…The following methods were found: branch and cut algorithm (5 papers) [14][15][16][17][18]; branch and price algorithm (2 papers) [19,20]; branch and bound algorithm (1 paper), [21] dynamic programming (5 papers) [22][23][24][25][26]; mixed integer linear programming (5 papers) [27][28][29][30][31]; experiments (1 paper) [32]; column generation scheme (4 papers) [33][34][35][36]; classical theory of programming and graph theory (1 paper) [37].…”

Section: Exact Methodsmentioning

confidence: 99%

Description of the classification of publications and the models used in solving of the vehicle routing problem with pickup and delivery

Silva

Zuluaga

2016

Rev. ing. univ. Medellín

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This review paper presents the description of the state of the art of the vehicle routing problem with pickups and deliveries, vrppd, product obtained from the literature review of most of the models reported in the international technical literature and used for many years by specialized researchers in the field. This classification considers the different solution methods, the treatment of the problem in time and future trends in its formulation, and proposal of new methods of solution, such as the metaheuristics caused by the complexity of the problem. Finally, several elements are left to discuss about existing and available tools for solving this problem.

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Many-to-many location-routing with inter-hub transport and multi-commodity pickup-and-delivery

Cited by 83 publications

References 42 publications

Heuristics for a hub location‐routing problem

Heuristics for a hub location‐routing problem

A branch-and-cut algorithm for the hub location and routing problem

Description of the classification of publications and the models used in solving of the vehicle routing problem with pickup and delivery

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