Volume 55, Number 5, September-October 2021
|Page(s)||2599 - 2614|
|Published online||23 September 2021|
An attractors-based particle swarm optimization for multiobjective capacitated vehicle routing problem
Université des Comores, Faculté des Sciences et Techniques, Département des Mathématiques, Physique, Chimie et Informatique, Laboratoire des Mathématiques, Statistiques et Informatique (LMSI), BP 2585 Moroni, Comoros
2 Agence pour la Sécurité de la Navigation Aérienne en Afrique et à Madagascar, Aeroport International Prince Said Ibrahim, Moroni, Comoros
Accepted: 4 August 2021
In this paper, a new multiobjective discrete particle swarm algorithm is presented for the Capacitated vehicle routing problem. The binary algorithm integrates particle displacement based on local attractors, a crowding distance as elitism policy and genetic operators. The proposed approach is first implemented on a set of well-known benchmarks for single-objective capacitated vehicle routing problems and compared to results underlined in the literature. The obtained results demonstrate its ability to achieve the main optimization solution and sometimes prove its efficiency from other given techniques. Then, the approach is applied to an academical example for the multiobjective Urban Bus Routing Problem with Route Balancing.
Mathematics Subject Classification: 90C29 / 90B20
Key words: Particle swarm optimization / multiobjective optimization / vehicle routing problems / urban bus routing problems / simultaneous pick-up and delivery
© The authors. Published by EDP Sciences, ROADEF, SMAI 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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