Authors: Consoli, Sergio
Moreno-Pérez, José
Darby-Dowman, Kenneth
Mladenović, Nenad 
Title: Discrete Particle Swarm Optimization for the minimum labelling steiner tree problem
Journal: Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)
Series/Report no.: Studies in Computational Intelligence
Volume: 129
First page: 313
Last page: 322
Issue Date: 18-Jun-2008
ISBN: 978-3-540-78986-4
ISSN: 1860-949X
DOI: 10.1007/978-3-540-78987-1_28
Particle Swarm Optimization is an evolutionary 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 evolution is obtained from the continuous movement of the particles that constitute the swarm submitted to the effect of the 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.
Publisher: Springer Link

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