Abstract
We introduce and discuss the methodology of the chaotic evolution (CE) algorithms, which is supported by a chaotic system. Because properties of the chaotic systems are the essential factors to influence the performance of the CE algorithms, we design and analyse several CE algorithms using different chaotic systems: logistic map, tent map, Gauss map and Henon map in a well-designed chaotic evolution framework. We propose a new CE algorithm using the combination of these chaotic systems to accelerate the convergence speed and improve convergence performance and analyse its effectiveness by comparing these new algorithms with our previous proposed CE algorithm with the logistic map. From the evaluation, our proposed CE helps the search to avoid the local optimum.
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