Communities of Local Optima as Funnels in Fitness Landscapes

Sebastian Herrmann (), Gabriela Ochoa () and Franz Rothlauf ()
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Sebastian Herrmann: Johannes Gutenberg University Mainz
Gabriela Ochoa: University of Stirling
Franz Rothlauf: Johannes Gutenberg University Mainz

No 1609, Working Papers from Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz

Abstract: We conduct an analysis of local optima networks extracted from ?tness landscapes of the Kauffman NK model under iterated local search. Applying the Markov Cluster Algorithm for community detection to the local optima networks, we ?nd that the landscapes consist of multiple clusters. This result complements recent ?ndings 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 optima networks offer a new way to characterize the multi-funnel structure of ?tness landscapes.

Keywords: Fitness landscape analysis; search difficulty; local optima networks; NK-landscapes. (search for similar items in EconPapers)
Pages: 7 pages
Date: 2016
New Economics Papers: this item is included in nep-cmp, nep-pr~ and nep-ure
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:jgu:wpaper:1609

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