基于动态行为选择的和声搜索算法

和声搜索算法是一种模拟音乐即兴创作过程的元启发式搜索,已成功应用于解决许多实际问题.针对高维函数优化问题,提出一种基于动态行为选择的和声搜索算法.在算法中新和声的即兴创作有3种策略,迭代过程中通过计算每个策略的即时价值和综合价值选择和声的即兴创作策略,并通过个体即兴创作策略选择方法提升寻优速度或避免陷入局部最优解.将所提出算法与9个改进和声搜索算法在22个基准函数上进行对比.实验结果表明,所提出算法具有较好的求解精度、稳定性和收敛速度,擅长于解决复杂的高维问题.

Harmony search algorithm based on dynamic behavior selection

Harmony search (HS) is a meta-heuristic algorithm imitating the music improvisation process, which has been successfully applied to many real-world problems. This paper presents a harmony search algorithm based on dynamic behavior selection (DBSHS) for solving high dimensional function optimization problems. Improvisation of a new harmony has three strategies in the DBSHS. In the process of iteration, the improvising behavior of the harmony is determined by calculating the immediate value and the comprehensive value of each strategy, individual improvising strategy selection method is proposed to improve the individual search speed or to avoid falling into the local optimal solution. The DBSHS is compared with nine variants of harmony search on 22 benchmark functions. The experimental results show that the proposed DBSHS has good solution accuracy, remarkable stability and high convergence speed. It is particularly good at solving complex high-dimensional problems.