Clustered population differential evolution approach to quadratic assignment problem

Davendra, Donald David; Zelinka, Ivan; Onwubolu, Godfrey

dc.title	Clustered population differential evolution approach to quadratic assignment problem	en
dc.contributor.author	Davendra, Donald David
dc.contributor.author	Zelinka, Ivan
dc.contributor.author	Onwubolu, Godfrey
dc.relation.ispartof	2009 IEEE Congress on Evolutionary Computation, Vols 1-5
dc.identifier.isbn	978-1-4244-2958-5
dc.date.issued	2009
dc.citation.spage	1224
dc.citation.epage	1231
dc.event.title	IEEE Congress on Evolutionary Computation
dc.event.location	Trondheim
utb.event.state-en	Norway
utb.event.state-cs	Norsko
dc.event.sdate	2009-05-18
dc.event.edate	2009-05-21
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	The Institute of Electrical and Electronics Engineers (IEEE)	en
dc.identifier.doi	10.1109/CEC.2009.4983085
dc.relation.uri	http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4983085
dc.description.abstract	An approach of population dynamics and clustering for permutative problems is presented in this paper. Diversity indicators are created from solution ordering and its mapping is shown as an advantage for population control in metaheuristics. Differential Evolution Algorithm is modified using this approach and vetted with the Quadratic Assignment Problem. Extensive experimentation is conducted on benchmark problems in this area.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1001797
utb.identifier.rivid	RIV/70883521:28140/09:63507975!RIV10-MSM-28140___
utb.identifier.obdid	43861060
utb.identifier.obdid	43861053
utb.identifier.scopus	2-s2.0-70449786573
utb.identifier.wok	000274803100163
utb.source	d-wok
dc.date.accessioned	2011-08-09T07:33:59Z
dc.date.available	2011-08-09T07:33:59Z
utb.contributor.internalauthor	Davendra, Donald David
utb.contributor.internalauthor	Zelinka, Ivan