Rigorous analyses for the combination of ant colony optimization and local search

dc.contributor.author	Neumann, Frank	de
dc.contributor.author	Sudholt, Dirk	de
dc.contributor.author	Witt, Carsten	de
dc.date.accessioned	2009-05-12T16:01:50Z
dc.date.available	2009-05-12T16:01:50Z
dc.date.issued	2008-03	de
dc.description.abstract	Ant colony optimization (ACO) is a metaheuristic that produces good results for a wide range of combinatorial optimization problems. Often such successful applications use a combination of ACO and local search procedures that improve the solutions constructed by the ants. In this paper, we study this combination from a theoretical point of view and point out situations where introducing local search into an ACO algorithm enhances the optimization process significantly. On the other hand, we illustrate the drawback that such a combination might have by showing that this may prevent an ACO algorithm from obtaining optimal solutions.	en
dc.identifier.uri	http://hdl.handle.net/2003/26150
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-8721
dc.language.iso	en	de
dc.relation.ispartofseries	Reihe CI; 243-08	de
dc.subject.ddc	004	de
dc.title	Rigorous analyses for the combination of ant colony optimization and local search	en
dc.type	Text	de
dc.type.publicationtype	report	de
dcterms.accessRights	open access

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