On the Optimization of Monotone Polynomials by Simple Randomized Search Heuristics

dc.contributor.authorWegener, Ingode
dc.contributor.authorWitt, Carstende
dc.date.accessioned2004-12-07T08:21:10Z
dc.date.available2004-12-07T08:21:10Z
dc.date.created2002de
dc.date.issued2003-06-04de
dc.description.abstractRandomized search heuristics like evolutionary algorithms and simulated annealing find many applications, especially in situations where no full information on the problem instance is available. In order to understand how these heuristics work, it is necessary to analyze their behavior on classes of functions. Such an analysis is performed here for the class of monotone pseudo-boolean polynomials. Results depending on the degree and the number of terms of the polynomial are obtained. The class of monotone polynomials is of special interest since simple functions of this kind can have an image set of exponential size, improvements can increase the Hamming distance to the optimum and in order to find a better search point, it can be necessary to search within a large plateau of search points with the same fitness value.en
dc.format.extent220592 bytes
dc.format.extent425130 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/2003/5425
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-5641
dc.language.isoende
dc.publisherUniversität Dortmundde
dc.relation.ispartofseriesReihe Computational Intelligence ; 141de
dc.subject.ddc004de
dc.titleOn the Optimization of Monotone Polynomials by Simple Randomized Search Heuristicsen
dc.typeTextde
dc.type.publicationtypereport
dcterms.accessRightsopen access

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