Multi-dimensional function optimization based on global-best harmony annealing algorithm
基于和声退火算法的多维函数优化

This paper put forward a kind of hybrid optimization algorithm:harmony annealing algorithm,which was based on harmony search and simulated annealing algorithm for multidimensional function optimization problem. Improved the algorithm the search mechanism of HS,selected the reasonable values about harmony memory considering rate(HMCR) and dynamic pitch adjusting rate(PAR). Searched the new vector randomly in the HM, then executed a Metropolis algorithm. It could improve the efficiency of the exploration and reduce the probability of trapped by local minimum value. The simulation results demonstrate the effectiveness and good quality of the proposed procedure,and better than those of harmony search and simulated annealing algorithm.