Shaping communities of local optima by perturbation strength

Citation

Herrmann S, Herrmann M, Ochoa G & Rothlauf F (2017) Shaping communities of local optima by perturbation strength. In: GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO 2017: Genetic and Evolutionary Computation Conference, Berlin, Germany, 15.07.2017-19.07.2017. New York: ACM, pp. 266-273. https://doi.org/10.1145/3071178.3071243

Abstract
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 perturbations or complete restarts are applied, with the middle ground of intermediate perturbation strengths largely unexplored.