Multi-population adaptive-gathering evolutionary algorithm in function optimization

Si-Duo Chen, Zhang-can Huang
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引用次数: 2

Abstract

The effect of population isolation is discussed by means of an analysis of the domains of attraction of local optima. Separation among populations and adaptive gathering of the initial population are achieved by local evolution, so as to transform the multi-modal function optimization into a uni-modal function optimization. Combining the space-division-based (/spl mu/+1) selection approach, which has a rapid convergence speed in uni-modal function optimization, a new evolutionary algorithm is presented to automatically separate and gather the initial population according to its domains of attraction. Numerical simulation results show the global searching ability of the new algorithm.
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函数优化中的多种群自适应聚集进化算法
通过对局部最优吸引域的分析,讨论了种群隔离的影响。通过局部进化实现种群间的分离和初始种群的自适应聚集,将多模态函数优化转化为单模态函数优化。结合单峰函数优化中收敛速度快的基于空间划分的(/spl mu/+1)选择方法,提出了一种根据吸引域自动分离和聚集初始种群的进化算法。数值仿真结果表明,该算法具有良好的全局搜索能力。
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