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Version vom 15. August 2009, 16:20 Uhr
Published: 2006
Dezember
Type: Technical Report
Nummer: 502
Institution: Institute AIFB University of Karlsruhe
Archivierungsnummer:1393
Kurzfassung
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
Evolutionäre Algorithmen, Parallele Algorithmen, Grid Computing, Multikriterielle Optimierung, Genetische Algorithmen, Naturanaloge Algorithmen, Optimierung