Dynamic Clonal and Chaos-Mutation Evolutionary Algorithm for Function Optimization

Authors:
Ming Yang;Jing Guan
Affiliations:
School of Computer Science, China University of Geosciences, Wuhan, China 430074;Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, China 430074
Venue:
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Year:
2008

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Abstract

This paper introduced a dynamic-clone and chaos-mutation evolutionary algorithm (DCCM-EA), which employs dynamic clone and chaos mutation methods, for function optimization. The number of clone is direct proportion to "affinity" between individuals and the chaos sequence can search the points all over the solution space, so DCCM-EA can make all points get equal evolutionary probability, to get the global optimal solution most possibly. In the experiments, taking 23 benchmark functions to test, it can be seen that DCCM-EA if effective for solving function optimization.