Authors: Consoli, Sergio
Moreno-Pérez, José A.
Darby-Dowman, Kenneth
Mladenović, Nenad 
Title: Discrete particle swarm optimization for the minimum labelling steiner tree problem
Journal: Natural Computing
Volume: 9
Issue: 1
First page: 29
Last page: 46
Issue Date: 1-Jan-2010
ISSN: 1567-7818
DOI: 10.1007/s11047-009-9137-9
Abstract: 
Particle Swarm Optimization is a population-based 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 labels.
Keywords: Combinatorial optimization | Discrete Particle Swarm Optimization | Graphs and networks | Heuristics | Minimum labelling Steiner tree problem
Publisher: Springer Link
Project: E.U. Marie Curie Fellowship for Early Stage Researcher Training, Grant no. MEST-CT-2004-006724
Spanish Government, Grant no. TIN2005-08404-C04-03
Canary Government, Grant no. PI042005/044

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