改进的新颖全局和声搜索算法

为了提高和声搜索算法的寻优性能,提出了改进的新颖全局和声搜索(INGHS)算法.通过差分向量范数定义和声记忆库多样性,以和声记忆库的多样性信息为指导实现位置动态更新,并结合变异操作更新和声记忆库.算法采用动态位置更新策略产生新和声,在寻优早期具有较好的全局搜索性能,在寻优后期具有较好的局部搜索性能,提高了算法跳出局部最优的能力.利用7个标准测试函数对所提算法与目前已知文献中优秀的改进HS算法进行性能测试,测试结果表明所提算法具有较好的寻优性能.

Improved Novel Global Harmony Search Algorithm

To improve the optimization performance of harmony search algorithm， an improved novel global harmony search (INGHS) algorithm was proposed. The harmony memory diversity was defined by the difference vector norm to implement dynamically position updating， and the mutation operation was employed to update harmony memory. A new harmony generated with dynamically updating strategy made the algorithm having excellent global search performance in the early states and local search capability during the final stages of the optimization process， which avoided the algorithm trapped in local optimal. Finally， the simulation for 7 benchmark functions were carried out using the proposed algorithm and other state-of-the-art HS variants that reported in the recent literature. The simulation results demonstrated that the proposed algorithm has a higher precision.