Harmony Search Optimization Algorithm Based on Normal Cloud

2013 ◽  
Vol 760-762 ◽  
pp. 1825-1830
Author(s):  
Li Fu Wang ◽  
Zhi Kong ◽  
Xin Gang Wang

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.

Author(s):  
Erwin Erwin ◽  
Saparudin Saparudin ◽  
Wulandari Saputri

This paper proposes a new method for image segmentation is hybrid multilevel thresholding and improved harmony search algorithm. Improved harmony search algorithm which is a method for finding vector solutions by increasing its accuracy. The proposed method looks for a random candidate solution, then its quality is evaluated through the Otsu objective function. Furthermore, the operator continues to evolve the solution candidate circuit until the optimal solution is found. The dataset used in this study is the retina dataset, tongue, lenna, baboon, and cameraman. The experimental results show that this method produces the high performance as seen from peak signal-to-noise ratio analysis (PNSR). The PNSR result for retinal image averaged 40.342 dB while for the average tongue image 35.340 dB. For lenna, baboon and cameramen produce an average of 33.781 dB, 33.499 dB, and 34.869 dB. Furthermore, the process of object recognition and identification is expected to use this method to produce a high degree of accuracy.


2009 ◽  
Vol 95 (4) ◽  
pp. 401-426 ◽  
Author(s):  
Prithwish Chakraborty, ◽  
Gourab Ghosh Roy ◽  
Swagatam Das ◽  
Dhaval Jain ◽  
Ajith Abraham

2013 ◽  
Vol 415 ◽  
pp. 353-356 ◽  
Author(s):  
Hong Gang Xia ◽  
Qing Liang Wang

Harmony search (HS) algorithm is a good meta-heuristic intelligent optimization method and it does depend on imitating the music improvisation process to generate a perfect state of harmony. However, intelligent optimization methods is easily trapped into local optimal, HS is no exception. In order to improve the performance of HS, a new variant of harmony search algorithm is proposed in this paper. The variant introduce a new crossover operation into HS, and design a strategy to adjust parameter pitch adjusting rate (PAR) and bandwidth (BW). Several standard benchmarks carried out to be tested. The numerical results demonstrated that the superiority of the proposed method to the HS and recently developed variants (IHS, and GHS).


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