Paper Info
Title
A Hybrid Particle Swarm Optimization Algorithm For The Capacitated Location Routing Problem
Abstract
Purpose The purpose of this paper is to solve the capacitated location routing problem (CLRP), which is an NP-hard problem that involves making strategic decisions as well as tactical and operational decisions, using a hybrid particle swarm optimization (PSO) algorithm.Design/methodology/approach PSO, which is a population-based metaheuristic, is combined with a variable neighborhood strategy variable neighborhood search to solve the CLRP.Findings The algorithm is tested on a set of instances available in the literature and gave good quality solutions, results are compared to those obtained by other metaheuristic, evolutionary and PSO algorithms.Originality/value Local search is a time consuming phase in hybrid PSO algorithms, a set of neighborhood structures suitable for the solution representation used in the PSO algorithm is proposed in the VNS phase, moves are applied directly to particles, a clear decoding method is adopted to evaluate a particle (solution) and there is no need to re-encode solutions in the form of particles after applying local search.
Year
DOI
Venue
2018
10.1108/IJICC-03-2017-0023
INTERNATIONAL JOURNAL OF INTELLIGENT COMPUTING AND CYBERNETICS
Keywords
Field
DocType
Particle swarm optimization, Variable neighbourhood search, Capacitated location routing problem
Particle swarm optimization,Population,Mathematical optimization,Variable neighborhood search,Computer science,Algorithm,Decoding methods,Local search (optimization),Metaheuristic
Journal
Volume
Issue
ISSN
11
1
1756-378X
Citations 
PageRank 
References 
1
0.35
22
Authors
3
Name
Order
Citations
PageRank
Laila Kechmane110.35
Benayad Nsiri284.65
Azeddine Baalal310.35