带有全局交叉的修正和声搜索算法  

A Modified Harmony Search Algorithm with Global Crossover

作　　者：王皓[1] 高立群[1] 欧阳海滨[1] 秦威[2] 

机构地区：[1]东北大学信息科学与工程学院,辽宁沈阳110819 [2]中国航天空气动力技术研究院,北京100074

出　　处：《东北大学学报（自然科学版）》2014年第8期1073-1077,共5页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(61273155);辽宁省科技厅博士科研启动基金资助项目(L201205118)

摘　　要：为增强和声搜索算法的全局搜索能力,提出一种带有全局交叉的修正和声搜索(MHSgc)算法.MHSgc算法采用多和声记忆库协同创作,应用邻域学习策略进行调整,取代原有的基音调整,从而增加了种群多样性.同时,提出一种全局交叉操作,并融合到MHSgc算法中,防止算法陷入局部最小.针对几个标准函数进行了实验仿真,数值结果表明,上述算法优于文献报道的8种智能算法(HS,IHS,GHS,NGHS,EHS,ITHS,MPSO,RMDE),具有较好的优化潜力.To improve the global search ability of a harmony search algorithm, a modified one with global crossover （MHSgc） was proposed. In the MHSgc, the collaborative improvisation of multiple-harmony-memory was applied. A neighbor-learning strategy replaced the intrinsic pitch adjusting, and thus the population diversity was increased. Moreover, global crossover operation was introduced into the MHSgc algorithm to avoid getting stuck into local minima. Simulations were carded out based on several benchmark functions. The results show that the proposed algorithm outperforms eight intelligent algorithms （IHS, GHS, NGHS, EHS, ITHS, MPSO, DE, ABC） reported in earlier literatures and has better optimization potential.

关 键 词：和声搜索算法 多和声记忆库 邻域学习 全局交叉 优化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]