Recherche à voisinage variable pour des problèmes de routage avec ou sans gestion de stock

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

A VNS-based Heuristic for Solving the Vehicle Routing Problem with Time Windows and Vehicle Preventive Maintenance Constraints

AbstractWe address a vehicle routing problem with time windows (VRPTW) that also contains vehicle with preventive maintenance constraints (VRPTW-PM) and propose a MIP mathematical formulation as well as a general variable neighborhood search metaheuristic (VNS) to solve with large instance the problematic situation. First we create a initial solution using Solomon heuristic then we minimize the number of used routes, and then the total travelled distance by all vehicles is minimized. Computational results show the efficiency of the proposed approach

Less is more approach: basic variable neighborhood search for the obnoxious p-median problem

The goal of the less is more approach (LIMA) for solving optimization problems that has recently been proposed in Mladenović et al. (2016) is to find the minimum number of search ingredients that make a heuristic more efficient than the currently best. In this paper, LIMA is successfully applied to solve the obnoxious p-median problem (OpMP). More precisely, we developed a basic variable neighborhood search for solving the OpMP, where the single search ingredient, the interchange neighborhood structure, is used. We also propose a new simple local search strategy for solving facility location problems, within the interchange neighborhood structure, which is in between the usual ones: first improvement and best improvement strategies. We call it facility best improvement local search. On the basis of experiments, it appeared to be more efficient and effective than both first and best improvement. According to the results obtained on the benchmark instances, our heuristic turns out to be highly competitive with the existing ones, establishing new state-of-the-art results. For example, four new best-known solutions and 133 ties are claimed in testing the set with 144 instances. © 2019 The Authors. International Transactions in Operational Research © 2019 International Federation of Operational Research Societies15YJC630097Higher Education Discipline Innovation ProjectMinistarstvo Prosvete, Nauke i TehnoloÅ¡kog Razvoja, MPNTR: BR05236839, 044006, 174010National Natural Science Foundation of China, NSFC: 71601065, 71690235, 71521001, 71871080, 71501058This research is partially supported by Serbian Ministry of Education, Science and Technological Development under the grants nos. 174010 and 044006. In addition, this research is partially supported by the framework of the grant number BR05236839 ?Development of information technologies and systems for stimulation of personality's sustainable development as one of the bases of development of digital Kazakhstan? and by the National Natural Science Foundation of China (Nos. 71871080, 71601065, 71690235, 71501058), Innovative Research Groups of the National Natural Science Foundation of China (71521001), the Humanities and Social Sciences Foundation of the Chinese Ministry of Education (No. 15YJC630097), and the Base of Introducing Talents of Discipline to Universities for Optimization and Decision-Making in the Manufacturing Process of Complex Product (111 project)

Variable neighborhood search for routing problems with or without inventory management

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

On the joint optimization of the periodic preventive maintenance and the spare parts inventory problem

International audienceIn this paper, we propose a new model for the joint optimization of the periodic preventive maintenance and spare parts inventory problem. It consist to find an optimal maintenance schedule of M machine over a cyclic horizon composed of τ periods with taking into account the inventory management of spare parts. A computational experiment was made on a set of instances generated to show the efficiency and the limit of our mode

Sequential variable neighborhood descent variants: an empirical study on the traveling salesman problem

International audienceIn a single local search algorithm, several neighborhood structuresare usually explored. The simplest way is todefine a single neighborhood as the union of all predefined neighborhood structures; the other possibility is tomake an order (or sequence) of the predefined neighborhoods,and to use them in the first improvement or thebest improvement fashion, following that order. In this work, first we classify possible variants of sequentialuse of neighborhoods and then, empirically analyze them in solving the classical traveling salesman problem(TSP). We explore the most commonly used TSP neighborhood structures, such as 2-opt and insertionneighborhoods. In our empirical study, we tested 76 differentsuch heuristics on 15,200 random test instances.Several interesting observations are derived. In addition, the two best of 76 heuristics (used as local searcheswithin a variable neighborhood search) are tested on 23 test instances taken from the TSP library (TSPLIB).It appears that the union of neighborhoods does not perform well