The effect of oscillating population size and re-initialization on the performance of genetic algorithms

Koumousis, VK; Katsaras, CP

dc.contributor.author	Koumousis, VK	en
dc.contributor.author	Katsaras, CP	en
dc.date.accessioned	2014-03-01T02:49:16Z
dc.date.available	2014-03-01T02:49:16Z
dc.date.issued	2002	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34464
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0036926922&partnerID=40&md5=ee444999abb22c9c6bf5d9a4a7362d5e	en
dc.subject	Genetic algorithms	en
dc.subject	Micro-GA	en
dc.subject	Variable population	en
dc.subject.other	Computational methods	en
dc.subject.other	Convergence of numerical methods	en
dc.subject.other	Modal analysis	en
dc.subject.other	Numerical methods	en
dc.subject.other	Optimization	en
dc.subject.other	Population statistics	en
dc.subject.other	Random processes	en
dc.subject.other	Theorem proving	en
dc.subject.other	Multimodal peak functions	en
dc.subject.other	Saw-tooth genetic algorithms	en
dc.subject.other	Variable population	en
dc.subject.other	Genetic algorithms	en
dc.title	The effect of oscillating population size and re-initialization on the performance of genetic algorithms	en
heal.type	conferenceItem	en
heal.publicationDate	2002	en
heal.abstract	Genetic Algorithms (GAs) are search algorithms based on the concepts of natural selection and survival of the fittest. A number of methods are developed, based on the standard GA scheme, to improve the robustness and computational efficiency of GAs. Moreover, an effort to categorize the developed methodologies devoted to the parameter control of evolutionary algorithms is presented. This paper proposes a GA that uses a variable population size in the form of a saw-tooth function, with a specific amplitude D and period of variation T.	en
heal.journalName	Proceedings of the Third International Conference on Engineering Computational Technology	en
dc.identifier.spage	185	en
dc.identifier.epage	186	en