Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport

Montréal, Canada

Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport

Montréal, Canada

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Nguyen P.K.,University of Montréal | Nguyen P.K.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Crainic T.G.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Toulouse M.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Toulouse M.,Oklahoma State University
Journal of Heuristics | Year: 2014

We propose a new population-based hybrid meta-heuristic for the periodic vehicle routing problem with time windows. This meta-heuristic is a generational genetic algorithm that uses two neighborhood-based meta-heuristics to optimize offspring. Local search methods have previously been proposed to enhance the fitness of offspring generated by crossover operators. In the proposed method, neighborhood-based meta-heuristics are used for their capacity to escape local optima, and deliver optimized and diversified solutions to the population of the next generation. Furthermore, the search performed by the neighborhood-based meta-heuristics repairs most of the constraint violations that naturally occur after the application of the crossover operators. The genetic algorithm we propose introduces two new crossover operators addressing the periodic vehicle routing problem with time windows. The two crossover operators are seeking the diversification of the exploration in the solution space from solution recombination, while simultaneously aiming not to destroy information about routes in the population as computing routes is NP-hard. Extensive numerical experiments and comparisons with all methods proposed in the literature show that the proposed methodology is highly competitive, providing new best solutions for a number of large instances. © 2014 Springer Science+Business Media New York.


Contardo C.,ESG UQAM | Cordeau J.-F.,HEC Montréal | Cordeau J.-F.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Gendron B.,University of Montréal | Gendron B.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport
Journal of Heuristics | Year: 2014

In this paper we present a three-phase heuristic for the Capacitated Location-Routing Problem. In the first stage, we apply a GRASP followed by local search procedures to construct a bundle of solutions. In the second stage, an integer-linear program (ILP) is solved taking as input the different routes belonging to the solutions of the bundle, with the objective of constructing a new solution as a combination of these routes. In the third and final stage, the same ILP is iteratively solved by column generation to improve the solutions found during the first two stages. The last two stages are based on a new model, the location-reallocation model, which generalizes the capacitated facility location problem and the reallocation model by simultaneously locating facilities and reallocating customers to routes assigned to these facilities. Extensive computational experiments show that our method is competitive with the other heuristics found in the literature, yielding the tightest average gaps on several sets of instances and being able to improve the best known feasible solutions for some of them. © 2013 Springer Science+Business Media New York.


Contardo C.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Hemmelmayr V.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Hemmelmayr V.,Vienna University of Economics and Business | Crainic T.G.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport
Computers and Operations Research | Year: 2012

In this paper, we introduce two algorithms to address the two-echelon capacitated location-routing problem (2E-CLRP). We introduce a branch-and-cut algorithm based on the solution of a new two-index vehicle-flow formulation, which is strengthened with several families of valid inequalities. We also propose an adaptive large-neighbourhood search (ALNS) meta-heuristic with the objective of finding good-quality solutions quickly. The computational results on a large set of instances from the literature show that the ALNS outperforms existing heuristics. Furthermore, the branch-and-cut method provides tight lower bounds and is able to solve small- and medium-size instances to optimality within reasonable computing times. © 2012 Elsevier Ltd. All rights reserved.


Hemmelmayr V.C.,Vienna University of Economics and Business | Hemmelmayr V.C.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Cordeau J.-F.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Cordeau J.-F.,HEC Montréal | Crainic T.G.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport
Computers and Operations Research | Year: 2012

In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP. © 2012 Elsevier Ltd. All rights reserved.


Anaya-Arenas A.M.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Anaya-Arenas A.M.,Laval University | Ruiz A.,Center Interuniversitaire Of Recherche Sur Les Reseaux Dentreprise La Logistique Et Le Transport | Ruiz A.,Laval University | And 2 more authors.
Proceedings of 2013 International Conference on Industrial Engineering and Systems Management, IEEE - IESM 2013 | Year: 2013

The emergency logistics field is a new and particular challenge for logistics' managers. In these networks, the satisfaction of the affected people's demand is much more important than the cost minimization. Moreover, crisis managers are looking for networks that ensure an equitable distribution of resources over affected people. We propose a new mathematical formulation that reflects this interest. First, we define a multi-period formulation for the network design problem, where the opening decisions are reconsidered at every period. In addition, this model includes different features of the realistic challenges of emergency logistics, like the possible shortage in capacity and the backorder of demand. Finally, three different formulations of a 'fair' distribution problem are proposed. These formulations are tested on random generated instances and the analysis of the distribution plans obtained with each formulation is presented at the end of this paper. © 2013 International Institute for Innovation, Industrial Engineering and Entrepreneurship - I4e2.

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