Journal of Siberian Federal University. Mathematics & Physics / Multiple Optima Identification Using Multi-strategy Multimodal Genetic Algorithm

Full text (.pdf)
Issue
Journal of Siberian Federal University. Mathematics & Physics. 2016 9 (2)
Authors
Sopov, Evgenii A.
Contact information
Sopov, Evgenii A.:Informatics and Telecommunications Institute Siberian State Aerospace University Krasnoyarsky Rabochy, 31, Krasnoyarsk, 660037 Russia;
Keywords
multimodal optimization; self-configuration; genetic algorithm; metaheuristic; niching
Abstract

Multimodal optimization (MMO) is the problem of finding many or all global and local optima. In this study, a novel approach based on a metaheuristic for designing multi-strategy genetic algorithm is proposed. The approach controls the interactions of many search techniques (different genetic algorithms for MMO) and leads to the self-configuring solving of problems with a priori unknown structure. The results of numerical experiments for classical benchmark problems and benchmark problems from the IEEE CEC competition on MMO are presented. The proposed approach has demonstrated efficiency better than standard niching techniques and comparable to advanced algorithms. The main feature of the approach is that it does not require the participation of the human-expert, because it operates in an automated, self-configuring way

Pages
246–257
Paper at repository of SibFU
https://elib.sfu-kras.ru/handle/2311/20249