A Simple But Effective Evolutionary Algorithm for Complicated Optimization Problems

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/4012

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DC Field	Value	Language
dc.creator	Xu, Y.G.	-
dc.creator	Liu, Guirong	-
dc.date	2003-12-23T03:00:41Z	-
dc.date	2003-12-23T03:00:41Z	-
dc.date	2002-01	-
dc.date.accessioned	2013-10-09T02:33:45Z	-
dc.date.available	2013-10-09T02:33:45Z	-
dc.date.issued	2013-10-09	-
dc.identifier	http://hdl.handle.net/1721.1/4012	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	A simple but effective evolutionary algorithm is proposed in this paper for solving complicated optimization problems. The new algorithm presents two hybridization operations incorporated with the conventional genetic algorithm. It takes only 4.1% ~ 4.7% number of function evaluations required by the conventional genetic algorithm to obtain global optima for the benchmark functions tested. Application example is also provided to demonstrate its effectiveness.	-
dc.description	Singapore-MIT Alliance (SMA)	-
dc.format	65862 bytes	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	High Performance Computation for Engineered Systems (HPCES);	-
dc.subject	evolutionary algorithm	-
dc.subject	optimization	-
dc.title	A Simple But Effective Evolutionary Algorithm for Complicated Optimization Problems	-
dc.type	Article	-
Appears in Collections:	MIT Items

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