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dc.contributor.authorWhitley, L. Darrellen
dc.contributor.authorSutton, Andrew M.en
dc.identifier.citationGECCO '09: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, held in Montreal, Quebec, 8-12 July, 2009: pp.381-388en
dc.description.abstractThis paper introduces a new component based model that makes it relatively simple to prove that certain types of landscapes are elementary. We use the model to reconstruct proofs for the Traveling Salesman Problem, Graph Coloring and Min-Cut Graph Partitioning. The same model is then used to efficiently compute the average values over particular partial neighborhoods for these same problems. For Graph Coloring and Min-Cut Graph Partitioning, this computation can be used to focus search on those moves that are most likely to yield an improving move, ignoring moves that cannot yield an improving move. Let x be a candidate solution with objective function value f(x). The mean value of the objective function over the entire landscape is denoted f. Normally in an elementary landscape one can only be sure that a neighborhood includes an improving move (assuming minimization) if f(x) > f. However, by computing the expected value of an appropriate partial neighborhood it is sometimes possible to know that an improving move exists in the partial neighborhood even when f(x) < f.en
dc.description.statementofresponsibilityL. Darrell Whitley and Andrew M. Suttonen
dc.rightsCopyright 2009 ACMen
dc.subjectFitness landscapes; elementary landscapesen
dc.titlePartial neighborhoods of elementary landscapesen
dc.typeConference paperen
dc.contributor.schoolSchool of Computer Scienceen
dc.contributor.conferenceGenetic and Evolutionary Computation Conference (11th : 2009 : Montreal, Canada)en
Appears in Collections:Computer Science publications

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