Computational Science Technical Note CSTN-160

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Random Flights for Particle Swarm Optimisers

A. V. Husselmann and K. A. Hawick

Archived: 2013

Abstract

Parametric Optimisation is an important problem that can be tackled with a range of bio-inspired problem space search algorithms. We show how a simplified Particle Swarm Optimiser (PSO) can exploit advanced space exploration with Levy flights, Rayleigh flights and Cauchy flights, and we discuss hybrid variations of these. We present implementations of these methods and compare algorithmic convergence on several multi-modal and uni-modal test functions. Random flights considerably enhance the PSO and the Levy flight gives good balance between local space exploration and local minima avoidance. We discuss computational tradeoffs involved in generating such flights.

Keywords: optimisation; multi-modal functions; flights; walks; swarms

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

@INPROCEEDINGS{CSTN-160,
        author = {A. V. Husselmann and K. A. Hawick},
        title = {Random Flights for Particle Swarm Optimisers},
        booktitle = {Proc. 12th IASTED Int. Conf. on Artificial Intelligence and Applications},
        year = {2013},
        pages = {15-22},
        address = {Innsbruck, Austria},
        month = {11-13 February},
        publisher = {IASTED},
        institution = {Computer Science, Massey University},
        keywords = {optimisation; multi-modal functions; flights; walks; swarms},
        owner = {kahawick},
        timestamp = {2012.08.24}
}


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