|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Peer Review Status:||Refereed|
|Title:||Communities of Local Optima as Funnels in Fitness Landscapes|
|Citation:||Herrmann S, Ochoa G & Rothlauf F (2016) Communities of Local Optima as Funnels in Fitness Landscapes In: Friedrich T (ed.) Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20 - 24, 2016, New York: ACM. GECCO 16: Genetic and Evolutionary Computation Conference 2016, 20.7.2016 - 24.7.2016, Denver, CO, USA, pp. 325-331.|
|Conference Name:||GECCO 16: Genetic and Evolutionary Computation Conference 2016|
|Conference Location:||Denver, CO, USA|
|Abstract:||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 optima networks offer a new way to characterize the multi-funnel structure of fitness landscapes.|
|Status:||Book Chapter: author post-print (pre-copy editing)|
|Rights:||Copyright 2016 Copyright held by the owner/author(s). Publication rights licensed to ACM.|
|HerrmannOR_FunnelsNK_GECCO16.pdf||1.56 MB||Adobe PDF||View/Open|
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