和声蛙跳算法在复杂优化问题中的应用研究

Harmony frog leaping algorithm and its application to complex optimization problems

和声搜索算法在求解复杂优化问题时,仅仅通过随机的方式产生新元素,搜索过程中新个体的有效性难以持续保证,影响算法的优化性能.针对该问题,将混合蛙跳算法的族群内部局部寻优模块嵌入和声搜索的算法框架中,将和声搜索算法的随机性与混合蛙跳算法的导向性相耦合.定义算法自适应调整参数并以此为基础对两种算法进行动态调用,从而实现两种算法的耦合动态搜索.将改进算法应用于标准测试函数和车辆路径问题的优化,模拟计算结果表明:本文提出的改进算法具有更强的全局搜索能力,得到的解更优,适合用于求解复杂优化问题.

When harmony search algorithm is used in solving complex optimization problems,it creates new elements via a random manner.This evolutionary strategy will affect the performance of the algorithm because the search process is difficult to ensure an effective individual.In response to these problems,shuffled frog leaping algorithm will be embedded in harmony search algorithm as a sub-part.The randomness of harmony search and the guidance of shuffled frog leaping algorithm are coupled.Adaptive factor is defined in this paper,and algorithms are invocated dynamically based on the factor so as to realize the coupling dynamic search.The improved algorithm is applied to the standard test functions and the optimization of VRP,the simulation results show that the improved algorithm has better global searching ability.Meanwhile it gets better solution and is suitable for solving complex optimization problems.