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Multi-Objective Particle Swarm Optimization on Computer Grids

Published: 2006 Dezember
Type: Technical Report
Nummer: 502
Institution: Institute AIFB University of Karlsruhe
Archivierungsnummer: 1393


In recent years, a number of authors have successfully extended particle swarm optimization to problem domains with multiple objectives. This paper addresses the issue of parallelizing multi-objective particle swarms. We propose and empirically compare two parallel versions which differ in the way they divide the swarm into subswarms that can be processed independently on different processors. One of the variants works asynchronously and is thus particularly suitable for heterogeneous computer clusters as occurring e.g. in modern grid computing platforms.

Download: Media:2006_1393_Mostaghim_Multi-Objective_1.pdf


Effiziente Algorithmen


Evolutionäre Algorithmen, Parallele Algorithmen, Grid Computing, Multikriterielle Optimierung, Genetische Algorithmen, Naturanaloge Algorithmen, Optimierung