Authors: Sergio Consoli José Andrés MorenoPérez Kenneth DarbyDowman Nenad Mladenović
Publish Date: 2009/06/17
Volume: 9, Issue: 1, Pages: 29-46
Abstract
Particle Swarm Optimization is a populationbased method inspired by the social behaviour of individuals inside swarms in nature Solutions of the problem are modelled as members of the swarm which fly in the solution space The improvement of the swarm is obtained from the continuous movement of the particles that constitute the swarm submitted to the effect of inertia and the attraction of the members who lead the swarm This work focuses on a recent Discrete Particle Swarm Optimization for combinatorial optimization called Jumping Particle Swarm Optimization Its effectiveness is illustrated on the minimum labelling Steiner tree problem given an undirected labelled connected graph the aim is to find a spanning tree covering a given subset of nodes whose edges have the smallest number of distinct labelsSergio Consoli was supported by an EU Marie Curie Fellowship for Early Stage Researcher Training ESTFP6 under grant number MESTCT2004006724 at Brunel University project NETACE The research of José Andrés MorenoPérez was partially supported by the projects TIN200508404C0403 of the Spanish Government with financial support from the European Union under the FEDER project and PI042005/044 of the Canary Government
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