Perhaps Not a Free Lunch But At Least a Free Appetizer

dc.contributor.author	Droste, Stefan	de
dc.contributor.author	Jansen, Thomas	de
dc.contributor.author	Wegener, Ingo	de
dc.date.accessioned	2004-12-07T08:19:29Z
dc.date.available	2004-12-07T08:19:29Z
dc.date.created	1998	de
dc.date.issued	1998-11-08	de
dc.description.abstract	It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in particular, in situations where not much is known about the objective function to be optimized. In contrast to that Wolpert and Macready (1997) proved that all optimization techniques have the same behavior - on average over all f : X -> Y where X and Y are finite sets. This result is called No Free Lunch Theorem. Here different scenarios of optimization are presented. It is argued why the scenario on which the No Free Lunch Theorem is based does not model real life optimization. For more realistic scenarios it is argued why optimization techniques differ in their efficiency. For a small example this claim is proved.	en
dc.format.extent	219741 bytes
dc.format.extent	578970 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/5339
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-5018
dc.language.iso	en	de
dc.publisher	Unversität Dortmund	de
dc.relation.ispartofseries	Reihe Computational Intelligence ; 45	de
dc.subject.ddc	004	de
dc.title	Perhaps Not a Free Lunch But At Least a Free Appetizer	en
dc.type	Text	de
dc.type.publicationtype	report
dcterms.accessRights	open access

Files

Now showing 1 - 2 of 2