0000000000146721

AUTHOR

Gabriela Ochoa

0000-0001-7649-5669

showing 3 related works from this author

Shaping communities of local optima by perturbation strength

2017

Recent work discovered that fitness landscapes induced by Iterated Local Search (ILS) may consist of multiple clusters, denoted as funnels or communities of local optima. Such studies exist only for perturbation operators (kicks) with low strength. We examine how different strengths of the ILS perturbation operator affect the number and size of clusters. We present an empirical study based on local optima networks from NK fitness landscapes. Our results show that a properly selected perturbation strength can help overcome the effect of ILS getting trapped in clusters of local optima. This has implications for designing effective ILS approaches in practice, where traditionally only small per…

Mathematical optimization021103 operations researchIterated local searchFitness landscapeComputer Science::Neural and Evolutionary Computation0211 other engineering and technologiesPerturbation (astronomy)02 engineering and technologyLocal optima networksLocal optimum0202 electrical engineering electronic engineering information engineeringPerturbation operator020201 artificial intelligence & image processingMathematicsProceedings of the Genetic and Evolutionary Computation Conference
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Communities of Local Optima as Funnels in Fitness Landscapes

2016

We conduct an analysis of local optima networks extracted from fitness landscapes of the Kauffman NK model under iterated local search. Applying the Markov Cluster Algorithm for community detection to the local optima networks, we find that the landscapes consist of multiple clusters. This result complements recent findings in the literature that landscapes often decompose into multiple funnels, which increases their difficulty for iterated local search. Our results suggest that the number of clusters as well as the size of the cluster in which the global optimum is located are correlated to the search difficulty of landscapes. We conclude that clusters found by community detection in local…

Mathematical optimization021103 operations researchMarkov chainFitness landscapeComputer scienceIterated local searchbusiness.industry0211 other engineering and technologies02 engineering and technologyLocal optimumGlobal optimum0202 electrical engineering electronic engineering information engineeringCluster (physics)020201 artificial intelligence & image processingArtificial intelligencebusinessProceedings of the Genetic and Evolutionary Computation Conference 2016
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Coarse-Grained Barrier Trees of Fitness Landscapes

2016

Recent literature suggests that local optima in fitness landscapes are clustered, which offers an explanation of why perturbation-based metaheuristics often fail to find the global optimum: they become trapped in a sub-optimal cluster. We introduce a method to extract and visualize the global organization of these clusters in form of a barrier tree. Barrier trees have been used to visualize the barriers between local optima basins in fitness landscapes. Our method computes a more coarsely grained tree to reveal the barriers between clusters of local optima. The core element is a new variant of the flooding algorithm, applicable to local optima networks, a compressed representation of fitnes…

Local optima networksTheoretical computer scienceFitness landscapeComputer scienceSearch difficulty0102 computer and information sciences02 engineering and technology01 natural sciencesLocal optimum0202 electrical engineering electronic engineering information engineeringCluster (physics)Disconnectivity graphRepresentation (mathematics)MetaheuristicNK-landscapesFlooding algorithmbusiness.industryFitness landscape analysisBig valleyLocal optima networksTree (data structure)010201 computation theory & mathematicsBarrier tree020201 artificial intelligence & image processingArtificial intelligencebusiness
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