【摘要】 针对和声搜索算法存在易陷入局部最优,导致提早收敛的缺点,提出一种融合局部搜索的和声搜索(LSHS)算法。将最优和声向量与在种群中随机选择的两个和声向量进行线性组合,生成一个新和声,扩大局部搜索区域,维持算法多样性,提高算法收敛速度。用9个标准测试函数对所提算法与HS和GHS算法进行实验比较,实验结果表明,LSHS算法的结果更优,性能更好。更多还原

【Abstract】 Harmony search(HS)algorithm tends to suffer from easiness of falling into local optimum,resulting in early convergence.Aiming at these disadvantages of the basic HS,an improved HS algorithm called local search technique fusion of harmony search(LSHS)algorithm was proposed.Linear combination of the best harmony vector and two vectors of harmonies randomly chosen in the population was proceeded to create a new harmony,thus expanding the local search area while the convergence rate was improved.In the experiments,the proposed algorithm was compared with HS and GHS algorithm on nine benchmark functions.Experimental results show that the LSHS algorithm is more effective.更多还原