基于反向计算和高斯分布估计的动态自适应和声搜索算法  

Dynamic Self-adaptive Harmony Search Algorithm Based on Opposition-based Computing and Gaussian Distribution Estimation

作　　者：拓守恒[1] 

机构地区：[1]陕西理工学院数学与计算机科学学院,陕西汉中723001

出　　处：《小型微型计算机系统》2013年第5期1158-1162,共5页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(81160183)资助

摘　　要：为了增强和声搜索算法在求解高维多模态问题时的空间全局探索能力和求解精度,通过定义的4种反向计算方法和高斯分布估计算法,提出一种动态自适应高维和声搜索算法.该算法采用正交试验初始化和声记忆库;利用多维动态自适应算法进行和声创作;采用动态反向选择算法更新和声记忆库,并改进和声音调微调调解步长,从而增强算法的空间探索能力,避免陷入局部搜索.通过6个标准的高维Benchmark函数测试表明,本文算法在全局搜索能力、收敛速度和求解精度等方面都有明显改进.In order to improve the global exploration ability and solving precision of harmony search （ HS ） algorithm, this paper presents a dynamic self-adaptive high-dimensional harmony search algorithm based on 4 Opposition-Based Computing （ OBC ） and Gaussian Distribution Estimation Algorithm （ GDEA ）. In the proposed algorithm, the orthogonal experimental design algorithm was used to initialize harmony memory （HM ） ; a multi-dimensional dynamic self-adaptive adjustment operator was employed to improvised a new harmony; harmony memory was selectively updated by dynamic opposition harmony vector; for avoiding the search being trapped in local optimum, an improved band width adjustment algorithm was employed to enhance the disturbance performance. Finally, extensive computational simulations and comparisons are carried out by employing 9 benchmark problems. The computational results show that the proposed algorithm is more effective in finding better solutions than the state-of-the-art harmony search algorithms.

关 键 词：反向计算 高斯分布估计 动态自适应 和声搜索算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]