A new evolutionary model for detecting multiple optima

Multimodal optimization problems consist in detecting all global and local optima of a problem. A new evolutionary approach to multimodal optimization called Roaming technique (RO) is presented. Roaming uses two original concepts in order to detect multiple optima: a stability measure for subpopulations and an external population called archive to store detected optima. Individuals in the archive are refined by evolving them independently. Performance of Roaming is compared by means of numerical experiments with two other evolutionary techniques. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—Heuristic methods General Terms Algorithms Keywords evolutionary multimodal optimization, stability measure

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Rodica Ioana Lung, D. Dumitrescu
• Keywords: GECCO 2007, Multimodal Optimization, Multimodal Optimization Problems, Roaming