Local optima networks and the performance of iterated local search

Abstract : Local Optima Networks (LONs) have been recently proposed as an alternative model of combinatorial fitness landscapes. The model compresses the information given by the whole search space into a smaller mathematical object that is the graph having as vertices the local optima and as edges the possible weighted transitions between them. A new set of metrics can be derived from this model that capture the distribution and connectivity of the local optima in the underlying configuration space. This paper departs from the descriptive analysis of local optima networks, and actively studies the correlation between network features and the performance of a local search heuristic. The NK family of landscapes and the Iterated Local Search metaheuristic are considered. With a statistically-sound approach based on multiple linear regression, it is shown that some LONs' features strongly influence and can even partly predict the performance of a heuristic search algorithm. This study validates the expressive power of LONs as a model of combinatorial fitness landscapes.
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Communication dans un congrès
Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference, Jul 2012, Philadelphia, United States. ACM, pp.369-376, 2012, <10.1145/2330163.2330217>


https://hal.archives-ouvertes.fr/hal-00741725
Contributeur : Sébastien Verel <>
Soumis le : lundi 15 octobre 2012 - 10:45:50
Dernière modification le : samedi 16 janvier 2016 - 01:10:23

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Fabio Daolio, Sébastien Verel, Gabriela Ochoa, Marco Tomassini. Local optima networks and the performance of iterated local search. Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference, Jul 2012, Philadelphia, United States. ACM, pp.369-376, 2012, <10.1145/2330163.2330217>. <hal-00741725>

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