Dynamic search initialisation strategies for multi-objective optimisation in peer-to-peer networks

Authors:
Ian Scriven;Andrew Lewis;Sanaz Mostaghim
Affiliations:
School of Engineering, Griffith University, Brisbane, Queensland, Australia;School of Information and Communication Technology, Griffith University, Brisbane, Queensland, Australia;Institute AIFB, University of Karlsruhe, Germany
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

Peer-to-peer based distributed computing environments can be expected to be dynamic to greater of lesser degree. While node losses will not usually lead to catastrophic failure of a population-based optimisation algorithm, such as particle swarm optimisation, performance will be degraded unless the lost computational power is replaced. When resources are replaced, one must consider how to utilise newly available nodes as well as the loss of existing nodes. In order to take advantage of newly available nodes, new particles must be generated to populate them. This paper proposes two methods of generating new particles during algorithm execution and compares the performance of each approach, then investigates a hybridised approach incorporating both mechanisms.