• English
    • français
  • Help
  •  | 
  • Contact
  •  | 
  • About
  •  | 
  • Login
  • HAL portal
  •  | 
  • Pages Pro
  • EN
  •  / 
  • FR
View Item 
  •   LillOA Home
  • Liste des unités
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
  • View Item
  •   LillOA Home
  • Liste des unités
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

An evolutionary algorithm for the vehicle ...
  • BibTeX
  • CSV
  • Excel
  • RIS

Document type :
Article dans une revue scientifique
DOI :
10.1016/j.ejor.2007.06.065
Title :
An evolutionary algorithm for the vehicle routing problem with route balancing
Author(s) :
Jozefowiez, Nicolas [Auteur]
LAAS-MOGISA
SEMET, Frédéric [Auteur]
LAGIS-OSL
Talbi, El-Ghazali [Auteur] refId
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Journal title :
European Journal of Operational Research
Pages :
761-769
Publisher :
Elsevier
Publication date :
2009-06-16
ISSN :
0377-2217
English keyword(s) :
Routing
Multi-objective optimization
Genetic algorithms
Parallel algorithms
HAL domain(s) :
Informatique [cs]/Recherche opérationnelle [cs.RO]
English abstract : [en]
In this paper, we address a bi-objective vehicle routing problem in which the total length of routes is minimized as well as the balance of routes, i.e. the difference between the maximal route length and the minimal route ...
Show more >
In this paper, we address a bi-objective vehicle routing problem in which the total length of routes is minimized as well as the balance of routes, i.e. the difference between the maximal route length and the minimal route length. We propose a meta-heuristic method based on an evolutionary algorithm involving classical multi-objective operators. To improve its efficiency, two mechanisms, which favor the diversification of the search, have been added. First, an elitist diversification mechanism is used in cooperation with classical diversification methodologies. Second, a parallel model designed to take into account the elitist diversification is proposed. Our method is tested on standard benchmarks for the vehicle routing problem. The contribution of the introduced mechanisms is evaluated by different performance metrics. All the experimentations indicate a strict improvement of the generated Pareto set.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Source :
Harvested from HAL
Université de Lille

Mentions légales
Université de Lille © 2017