Bratton, Daniel. 2010. Simple and Adaptive Particle Swarms. Doctoral thesis, Goldsmiths, University of London [Thesis]

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Abstract or Description

The substantial advances that have been made to both the theoretical and practical aspects of particle
swarm optimization over the past 10 years have taken it far beyond its original intent as a biological
swarm simulation. This thesis details and explains these advances in the context of what has been
achieved to this point, as well as what has yet to be understood or solidified within the research community.
Taking into account the state of the modern field, a standardized PSO algorithm is defined for
benchmarking and comparative purposes both within the work, and for the community as a whole.

This standard is refined and simplified over several iterations into a form that does away with potentially
undesirable properties of the standard algorithm while retaining equivalent or superior performance
on the common set of benchmarks. This refinement, referred to as a discrete recombinant swarm (PSODRS)
requires only a single user-defined parameter in the positional update equation, and uses minimal
additive stochasticity, rather than the multiplicative stochasticity inherent in the standard PSO. After a
mathematical analysis of the PSO-DRS algorithm, an adaptive framework is developed and rigorously
tested, demonstrating the effects of the tunable particle- and swarm-level parameters. This adaptability
shows practical benefit by broadening the range of problems which the PSO-DRS algorithm is wellsuited
to optimize.

Item Type:	Thesis (Doctoral)
Keywords:	particle swarms, algorithm, PSO, adaptive, stochasticity
Departments, Centres and Research Units:	Computing
Date:	4 October 2010
Item ID:	4752
Date Deposited:	09 Jan 2012 13:36
Last Modified:	08 Sep 2022 08:22
URI:	https://research.gold.ac.uk/id/eprint/4752

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