Conference Proceeding

Unexplained Fluctuations in Particle Swarm Optimisation Performance with Increasing Problem Dimensionality

Details

Citation

Graham K, Thomson S & Brownlee A (2023) Unexplained Fluctuations in Particle Swarm Optimisation Performance with Increasing Problem Dimensionality. In: GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation. The Genetic and Evolutionary Computation Conference (GECCO) 2023, Lisbon, 15.07.2023-19.07.2023. New York: ACM, pp. 67-68.

Abstract
We study the behaviour of particle swarm optimisation (PSO) with increasing problem dimension for the Alpine 1 function as an exploratory and preliminary case study. Performance trends are analysed and the tuned population size for PSO across dimensions is considered. While performance generally decreases monotonically with scale, there is an unexpected improvement in performance part way along the trend. This also appears to coincide with a counter-intuitive transition from large to small populations being preferred, and underlines the challenge, and importance of, selecting the right algorithm and configuration for the problem at each increase in dimensionality.

StatusPublished
Publication date31/12/2023
Publication date online24/07/2023
URLhttp://hdl.handle.net/1893/35280
PublisherACM
Place of publicationNew York
ISBN979-8-4007-0120-7
ConferenceThe Genetic and Evolutionary Computation Conference (GECCO) 2023
Conference locationLisbon
Dates

People (1)

Dr Sandy Brownlee

Dr Sandy Brownlee

Senior Lecturer in Computing Science, Computing Science and Mathematics - Division

Research centres/groups