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.
stability measure evolutionary multimodal optimization