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The pitch adjusting rate (PAR) is an important parameter in harmony search algorithm, which indicates that the algorithm will choose a neighboring value with a probability. The traditional harmony search algorithm uses fixed value for PAR. However, PAR should be increased when all objective values are centralized and decreased when the function values are scattered in the solution space. In this paper, a new cloud harmony search algorithm (CHS) is proposed. We introduce cloud model theory to adjust the value PAR in the harmony search to improve the global search ability and make faster convergence speed of the algorithm. The improved harmony search algorithm is tested on some benchmark functions and the results are compared with the result of the traditional harmony search. Experimental results indicate that the improved harmony search algorithm has a good performance in the global search ability and convergent speed.

Harmony Search Optimization Algorithm Based on Normal Cloud