A Clustering Based Niching EA for Multimodal Search Spaces

Abstract. We propose a new niching method for Evolutionary Algorithms which is able to identify and track global and local optima in a multimodal search space. To prevent the loss of diversity we replace the global selection pressure within a single population by local selection of a multi-population strategy. The sub-populations representing species specialized on niches are dynamically identified using standard clustering algorithms on a primordial population. With this multi-population strategy we are able to preserve diversity within the population and to identify global/local optima directly without further post-processing.

• Type: Conference
• Year: 2003
• Where: AE
• Authors: Felix Streichert, Gunnar Stein, Holger Ulmer, Andreas Zell
• Keywords: AE 2003, Artificial Intelligence, Global Selection Pressure, Multi-population Strategy, Multimodal Search Space