Local Optima Networks, Landscape Autocorrelation and Heuristic Search Performance

Abstract : Recent developments in fitness landscape analysis include the study of Local Optima Networks (LON) and applications of the Elementary Landscapes theory. This paper represents a first step at combining these two tools to explore their ability to forecast the performance of search algorithms. We base our analysis on the Quadratic Assignment Problem (QAP) and conduct a large statistical study over 600 generated instances of different types. Our results reveal interesting links between the network measures, the autocorrelation measures and the performance of heuristic search algorithms.
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Communication dans un congrès
Coello, CarlosA.Coello and Cutello, Vincenzo and Deb, Kalyanmoy and Forrest, Stephanie and Nicosia, Giuseppe and Pavone, Mario. Parallel Problem Solving from Nature - PPSN XII, Sep 2012, Taormina, Italy. Springer Berlin Heidelberg, 7492, pp.337-347, 2012, Lecture Notes in Computer Science. <10.1007/978-3-642-32964-7_34>
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Soumis le : lundi 15 octobre 2012 - 13:56:34
Dernière modification le : samedi 16 janvier 2016 - 01:10:23
Document(s) archivé(s) le : samedi 17 décembre 2016 - 01:25:57

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Francisco Chicano, Fabio Daolio, Gabriela Ochoa, Sébastien Verel, Marco Tomassini, et al.. Local Optima Networks, Landscape Autocorrelation and Heuristic Search Performance. Coello, CarlosA.Coello and Cutello, Vincenzo and Deb, Kalyanmoy and Forrest, Stephanie and Nicosia, Giuseppe and Pavone, Mario. Parallel Problem Solving from Nature - PPSN XII, Sep 2012, Taormina, Italy. Springer Berlin Heidelberg, 7492, pp.337-347, 2012, Lecture Notes in Computer Science. <10.1007/978-3-642-32964-7_34>. <hal-00741842>

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