Multi-Swarm optimization for dynamic combinatorial problems: A case study on dynamic vehicle routing problem

Abstract : Many combinatorial real-world problems are mostly dynamic. They are dynamic in the sense that the global optimum location and its value change over the time, in contrast to static problems. The task of the optimization algorithm is to track this shifting optimum. Particle Swarm Optimization (PSO) has been previously used to solve continuous dynamic optimization problems, whereas only a few works have been proposed for combinatorial ones. One of the most interesting dynamic problems is the Dynamic Vehicle Routing Problem (DVRP). This paper presents a Multi-Adaptive Particle Swarm Optimization (MAPSO) for solving the Vehicle Routing Problem with Dynamic Requests (VRPDR). In this approach the population of particles is split into a set of interacting swarms. Such a multi-swarm helps to maintain population diversity and good tracking is achieved. The effectiveness of this approach is tested on a well-known set of benchmarks, and compared to other metaheuristics from literature. The experimental results show that our multi-swarm optimizer significantly outperforms single solution and population based metaheuristics on this problem.
Type de document :
Communication dans un congrès
Springer. Ants 2010: Seventh International Conference on Swarm Intelligence, Sep 2010, Bruxelles, Belgium. Springer, 6234, pp.227-238, 2010, LNCS. 〈10.1007/978-3-642-15461-4_20〉
Liste complète des métadonnées

https://hal.inria.fr/hal-00690620
Contributeur : Ist Rennes <>
Soumis le : mardi 24 avril 2012 - 09:00:53
Dernière modification le : jeudi 11 janvier 2018 - 06:22:13

Identifiants

Citation

Mostepha Redouane Khouadjia, Enrique Alba, Laetitia Jourdan, El-Ghazali Talbi. Multi-Swarm optimization for dynamic combinatorial problems: A case study on dynamic vehicle routing problem. Springer. Ants 2010: Seventh International Conference on Swarm Intelligence, Sep 2010, Bruxelles, Belgium. Springer, 6234, pp.227-238, 2010, LNCS. 〈10.1007/978-3-642-15461-4_20〉. 〈hal-00690620〉

Partager

Métriques

Consultations de la notice

253