Information Management Department Chung Yuan Christian University Chun li, Taiwan

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Abstract—Differential evolution, termed DE, is a novel and rapidly developed evolution computation in recent years. There are some advantages of DE, including simple structure, easy use and rapid convergence speed. Besides, DE can be also applied on the complex optimization problem. However, there are some issues, such as premature convergence and stagnation, remaining in DE algorithm. To overcome those disadvantages, a different method was proposed, named CO-DE, by combining with a simple coevolutionary model and reset mechanism. Thus, CO-DE can maintain appropriate swarm diversity and reduce the premature convergence. On the other hand, a reset mechanism was set to avoid the particle stagnates, which can further improve the performance of differential evolution. The proposed model can be now successfully applied with some well-known benchmark functions.

Index Terms—Differential Evolution; Evolutionary Computation; Co-evolutionary; Global optimization

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Cite: Wei-Ping Lee and Wan-Jou Chien, "A Novel Differential Evolution with Co-evolution Strategy," Journal of Computers vol. 6, no. 3, pp. 594-602, 2011.