安徽大学学报（自然科学版）Issue(3)：32-36,5.DOI:10.3969/j.issn.1000-2162.2014.03.006
混沌差分进化算法在复杂优化问题中的应用研究
Research on chaos differential evolution algorithm and its application to complex optimization problems
摘要
Abstract
When differential evolution algorithm is used in solving the complex optimization problems, diversity of species is decreased in the later evolution period, therefore the algorithm can easily fall into local optimum. A novel chaos differential evolution algorithm based on the differential evolution and chaos optimization algorithm, which made use of the ergodicity and internal randomness of chaos iterations, was presented to overcome the defect of premature local optimum and enhance the global searching capacity of differential evolution with that of powerful local searching capacity of the chaos optimization algorithm. The experimental results indicated that the chaos differential evolution algorithm could improve the global searching capacity significantly and avoid falling into local optimum. Thus, the proposed approach was more feasible and effective in solving the complex optimization problem compared with differential evolution and chaos optimization algorithm.关键词
复杂优化问题/遗传算法/混沌映射/混沌遗传算法Key words
complex optimization problems/differential evolution algorithm/chaotic map/chaos differential evolution algorithm分类
信息技术与安全科学引用本文复制引用
肖文显,许利军,马孝琴..混沌差分进化算法在复杂优化问题中的应用研究[J].安徽大学学报（自然科学版）,2014,(3):32-36,5.基金项目
国家自然科学基金资助项目(71171151) （71171151）
河南省教育厅自然科学基金资助项目(13B520011) （13B520011）
