Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/87942
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dc.contributor.authorParkinson, E.en
dc.contributor.authorGhandar, A.en
dc.contributor.authorMichalewicz, Z.en
dc.contributor.authorTuson, A.en
dc.date.issued2011en
dc.identifier.citationProceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011 / pp.135-136en
dc.identifier.isbn9781450306904en
dc.identifier.urihttp://hdl.handle.net/2440/87942-
dc.description.abstractTo improve evolutionary algorithm performance, this paper proposes a strategy to aid ascent and to help avoid premature convergence. Rapid increases in population fitness may result in premature convergence and sub optimal solution. A thresholding mechanism is proposed which discards child solutions only if their fitnesses are either too bad, in which case they are discarded, nor too good, in which case they pose the danger of premature convergence. This strategy is evaluated using two combinatorial optimization problems: the classic TSP benchmark and the more constrained vehicle routing problem (VRP) benchmark. The idea offers a relatively straight forward method for adding value by improving both runtime or solution quality. We consider a stochastic hill climber and a population based heuristic (an evolutionary algorithm).en
dc.description.statementofresponsibilityEddy Parkinson, Adam Ghandar, Zbigniew Michalewicz, Andrew Tusonen
dc.language.isoenen
dc.publisherACMen
dc.source.urihttp://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2011c.htmlen
dc.titleControlling the tradeoff between time and quality by considering the reproductive potential of offspringen
dc.typeConference paperen
dc.identifier.rmid0020115413en
dc.contributor.conferenceGenetic and Evolutionary Computation Conference (GECCO) (12 Jul 2011 - 16 Jul 2011 : Dublin)en
dc.identifier.doi10.1145/2001858.2001935en
dc.publisher.placeonlineen
dc.relation.granthttp://purl.org/au-research/grants/arc/DP0985723en
dc.identifier.pubid26458-
pubs.library.collectionComputer Science publicationsen
pubs.library.teamDS01en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
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