基于全局最优的自适应和声搜索算法

针对传统和声算法收敛速度慢和搜索精度低等固有缺点,提出一种改进的自适应全局最优和声搜索算法.在即兴创作方案中,带宽由当前和声里的最优和声变量和最差和声变量之差表示,使得带宽具有针对具体情况的自适应能力,并且每次保存最优和声中一个随机和声变量.在产生的随机数大于和声记忆库存储考虑概率时,利用种群内差分随机生成一个和声变量...

Adaptive harmony search algorithm based on global optimization

An adaptive harmony search algorithm utilizing global optimal mechanism (AGOHS) was proposed to overcome the drawbacks of harmony search (HS) algorithm, such as slow convergence speed and low search accuracy. The modifications of AGOHS was classified into the following aspects. In the improvisation phase, the bandwidth (BW) was represented by the difference between the optimal harmony variable and the worst harmony variable in the current harmony, so that the BW had the ability to adapt to specific situations, and saved a random harmony variable in the optimal harmony every time. A novel harmony variable was generated randomly by using the intra population difference while the obtained random number was greater than the reconciliation probability of harmony memory storage. To improve the search ability and the robustness, a novel harmony was randomly generated from the minimum value to the maximum value of harmony in the current population. The best harmony with the smallest error among the gained harmonies in this phase was selected and used to update the harmony memory. The proposed algorithm was compared with three improved harmony search algorithms on 13 test functions, experimental results revealed that the AGOHS had better global search capability and convergence speed.