Particle swarm optimization with an oscillating inertia weight

Kyriakos Kentzoglanakis, Matthew Poole

Research output: Contribution to conferencePaperpeer-review

212 Downloads (Pure)

Abstract

In this paper, we propose an alternative strategy of adapting the inertia weight parameter during the course of particle swarm optimization. Three oscillating inertia weight functions of time are presented and their influence on the performance and success of the algorithm is investigated by optimizing six standard benchmark functions. Instances of the algorithm that make use of inertia weight adaptation schemes from the literature are also tested for comparison purposes. The results show that the proposed functions are competitive and, in some cases, outperform the established inertia weight functions, in terms of consistency and speed of convergence.
Original languageEnglish
Publication statusPublished - 2009
Event11th Annual Conference on Genetic and Evolutionary Computation - Montreal, Canada
Duration: 8 Jul 200912 Jul 2009

Conference

Conference11th Annual Conference on Genetic and Evolutionary Computation
Abbreviated titleGECCO '09
CountryCanada
CityMontreal
Period8/07/0912/07/09

Fingerprint

Dive into the research topics of 'Particle swarm optimization with an oscillating inertia weight'. Together they form a unique fingerprint.

Cite this