An Empirical Analysis of Evolutionary Particle Swarm Optimization

dc.rights.license	CC-BY-NC-ND
dc.contributor.advisor	Vreeswijk, dr. G.A.W.
dc.contributor.author	Hoek, J. van
dc.date.accessioned	2018-01-17T18:01:08Z
dc.date.available	2018-01-17T18:01:08Z
dc.date.issued	2018
dc.identifier.uri	https://studenttheses.uu.nl/handle/20.500.12932/28401
dc.description.abstract	Evolutionary Particle Swarm Optimization (EPSO) is a combination of Classic Particle Swarm Optimization and Evolutionary Algorithms. In this thesis we recreate the original EPSO algorithm and analyze its performance. Furthermore we extend the algorithm with uniform recombination, another idea from Evolutionary Algorithms. Finally we analyze why EPSO performs so well, and whether our extension fixes the mistakes made by EPSO or not.
dc.description.sponsorship	Utrecht University
dc.format.extent	1597208
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.title	An Empirical Analysis of Evolutionary Particle Swarm Optimization
dc.type.content	Master Thesis
dc.rights.accessrights	Open Access
dc.subject.keywords	Particle Swarm Optimization; Evolutionary Computing; Evolutionary Particle Swarm Optimization; PSO; EPSO; EA
dc.subject.courseuu	Artificial Intelligence