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多维函数优化中遗传和声算法的应用 被引量:1

Genetic Harmony Algorithms for Solving Optimization Problems
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摘要 在研究遗传算法解决多维函数优化问题的基础上,结合一种新近出现的智能优化算法——和声搜索算法,提出遗传和声混合优化算法。新算法运用遗传的交叉和变异操作对初始种群进行进化,产生次优种群,再利用和声的取值概率HMCR和微调概率PAR对该种群进行搜索获得较高质量的新种群。仿真实验表明,新算法提高了求解质量、跳出局部极小的能力得到了进一步提升。 A kind of hybrid optimization algorithm--Genetic harmony algorithm ,which is based on Genetic algorithm and harmony search for multidimensional function optimization problem is put forward. The new algorithm used crossover and mutation operators of GA on evolution of initial population, and Harmony Memory Considering Rate(HMCR) and Pitch Adjusting Rate (PAR) of HS to search high quality of new species. The simulation results demonstrate the effectiveness and good quality of the proposed procedure.
作者 张风荣
出处 《科技通报》 北大核心 2016年第3期8-11,16,共5页 Bulletin of Science and Technology
基金 国家自然科学基金(10871116) 山东省课题(J15LN78) 院级课题:2015LG001
关键词 遗传算法 和声搜索 遗传和声算法 函数优化 genetic algorithm harmony search genetic harmony algorithn function optimization
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