Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/84699

Title

A heterogeneous particle swarm

Author(s)

Cartwright, Luke;  Hendtlass, Tim

Abstract

Almost all Particle Swarm Optimisation (PSO) algorithms use a number of identical, interchangeable particles that show the same behaviour throughout an optimisation. This paper describes a PSO algorithm in which the particles, while still identical, have two possible behaviours. Particles are not interchangeable as they make independent decisions when to change between the two possible behaviours. The difference between the two behaviours is that the attraction towards a particle’s personal best in one is changed in the other to repulsion from the personal best position. Results from experiments on three standard functions show that the introduction of repulsion enables the swarm to sequentially explore optima in problem space and enables it to outperform a conventional swarm with continuous attraction.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Faculty of Information and Communication Technologies

Source

Lecture notes in computer science: Artificial Life: Borrowing from Biology: proceedings of the 4th Australian Conference, Melbourne, Australia, 01-04 December 2009. / K. Korb, M. Randall, and T. Hendtlass (eds.), Vol. 5865, pp. 201-210

Publication year

2009

FOR Code(s)

010303 Optimisation;  080108 Neural, Evolutionary and Fuzzy Computation

Keyword(s)

Collective intelligence;  Optimisation;  Particle swarm optimisation

Publisher

Springer

ISSN

0302-9743

ISBN

9783642104268, 3642104266

Publisher URL

http://dx.doi.org/10.1007/978-3-642-10427-5_20

Copyright

Copyright © 2009 Springer-Verlag Berlin Heidelberg.

Peer reviewed