An Automatic Control Parameters Tuning Method for Differential Evolution
Satoshi Yamaguchi · IEEJ Transactions on Electronics Information and Systems · 2008
Differential Evolution(DE) is one of the evolutionary algorithms, and has shown excellent ability for solving global optimization problems over continuous spaces. DE has a few control parameters that have to be set by users. The ability of DE is depending on these control parameters, and, in many cases, trial-and-error process are required for finding suitable parameters. This paper proposes a method for tuning the DE control parameters automatically. The proposed method tunes control parameters within DE search process. By using this method, trial-and-error processes for finding appropriate control parameters are not required. To evaluate the performance, the proposed method was applied to 9 benchmark function optimization problems. The results indicate that the proposed method shows 100% feasibility to solving the optimization problems without outstanding increase of generations required for finding the optimum solutions.