An improved particle swarm optimization algorithm for the capacitated location routing problem and for the location routing problem with stochastic demands

[Display omitted] •An improved variant of the particle swarm optimization algorithm is presented.•A new formulation of the location routing problem with stochastic demands is given.•A new neighborhood topology for PSO suitable for combinatorial optimization problems is proposed.•The proposed algorit...

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Veröffentlicht in:	Applied soft computing Jg. 37; S. 680 - 701
1. Verfasser:	Marinakis, Yannis
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.12.2015
Schlagworte:	Capacitated location routing problem Combinatorial neighborhood topology Expanding neighborhood topology Global and local neighborhood topology Location routing problem with stochastic demands Particle swarm optimization Location routing problem with stochastic demands Expanding neighborhood topology Global and local neighborhood topology Particle swarm optimization Combinatorial neighborhood topology Capacitated location routing problem
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
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Zusammenfassung:	[Display omitted] •An improved variant of the particle swarm optimization algorithm is presented.•A new formulation of the location routing problem with stochastic demands is given.•A new neighborhood topology for PSO suitable for combinatorial optimization problems is proposed.•The proposed algorithm is tested in the CLRP and in the LRPSDs.•Comparisons with other algorithms from the literature are performed. In this paper, a new version of the particle swarm optimization (PSO) algorithm suitable for discrete optimization problems is presented and applied for the solution of the capacitated location routing problem and for the solution of a new formulation of the location routing problem with stochastic demands. The proposed algorithm combines three different topologies which are incorporated in a constriction particle swarm optimization algorithm and, thus, a very effective new algorithm, the global and local combinatorial expanding neighborhood topology particle swarm optimization, was developed. The algorithm was tested, initially, in the three classic sets of benchmark instances for the capacitated location routing problem with discrete demands and, then, as there are no benchmark instances for the location routing problem with stochastic demands, these instances were transformed appropriately in order to be suitable for the problem with stochastic demands. The algorithm was tested in the problem with the stochastic demands using these transformed sets of benchmark instances. The algorithm was compared with a number of different implementations of the PSO and with metaheuristic, evolutionary and nature inspired algorithms from the literature for the location routing problem with discrete and stochastic demands.
ISSN:	1568-4946 1872-9681
DOI:	10.1016/j.asoc.2015.09.005