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dc.contributor.authorSilva, Carlos A.
dc.contributor.authorRunkler, Thomas A.
dc.contributor.editorBrinkschulte, Uwe
dc.contributor.editorBecker, Jürgen
dc.contributor.editorFey, Dietmar
dc.contributor.editorGroßpietsch, Karl-Erwin
dc.contributor.editorHochberger, Christian
dc.contributor.editorMaehle, Erik
dc.contributor.editorRunkler, Thomas A.
dc.date.accessioned2019-10-30T11:53:38Z
dc.date.available2019-10-30T11:53:38Z
dc.date.issued2004
dc.identifier.isbn3-88579-370-9
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/29374
dc.description.abstractThis paper addresses the optimization of a dynamic Traveling Salesman Problem using the Ant Colony Optimization algorithm. Ants are social insects with limited skills that live in colonies able to solve complex problems. The intelligence of the global society arises from self organization mechanisms, based on the indirect communication between individuals through pheromones. The routing problem here presented is a typical case that requires a self organization type of algorithm, in order to cope with the problem dynamics. The simulation results show how the ant colony optimization is able to solve the different possible routing cases.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofARCS 2004 – Organic and pervasive computing
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-41
dc.titleAnt colony optimization for dynamic traveling salesman problemsen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages259-266
mci.conference.sessiontitleRegular Research Papers
mci.conference.locationAugsburg
mci.conference.dateMarch 26, 2004


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