Browse > Article
http://dx.doi.org/10.5391/JKIIS.2011.21.3.401

Study on Improvement of Convergence in Harmony Search Algorithms  

Lee, Sang-Kyung (중앙대학교 전자전기공학부)
Ko, Kwang-Enu (중앙대학교 전자전기공학부)
Sim, Kwee-Bo (중앙대학교 전자전기공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.21, no.3, 2011 , pp. 401-406 More about this Journal
Abstract
In order to solve a complex optimization problem more efficiently than traditional approaches, various meta-heuristic algorithms such as genetic algorithm, ant-colony algorithm, and harmony search algorithm have been extensively researched. Compared with other meta-heuristic algorithm, harmony search algorithm shows a better result to resolve the complex optimization issues. Harmony search algorithm is inspired by the improvision process of musician for most suitable harmony. In general, the performance of harmony search algorithm is determined by the value of harmony memory considering rate, and pitch adjust rate. In this paper, modified harmony search algorithm is proposed in order to derive best harmony. If the optimal solution of a specific problem can not be found for a certain period of time, a part of original harmony memory is updated as the selected suitable harmonies. Experimental results using test function demonstrate that the updated harmony memory can induce the approximation of reliable optimal solution in the short iteration, because of a few change of fitness.
Keywords
Harmony search algorithm; optimization; Meta Heuristic; global optimum; local minimum;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Marco Dorigo, Vittorio Maniezzo, Alberto Colorni, "The Ant System: Optimization by a colony of cooperating agents," Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 26, Issue 1, pp. 29-41, 1996.   DOI
2 Kennedy, J., Eberhart, R., "Particle swarm optimization," Neural Networks,1995. Proceedings., IEEE International Conference on, vol. 4, pp. 1942-1948, 1995.   DOI
3 Zong Woo Geem, Joong Hoon Kim, G.V. Loganathan, "new heuristic optimization algorithm: harmony search," Simulation, vol. 76, pp.60-68, 2001.   DOI
4 L. Bianchi, M. Dorigo, L. M. Gambardella, W. J. Gutjahr, "A survey on metaheuristics for stochastic combinatorial optimization," Natural Computing, vol. 8, pp.239-287, 2009   DOI
5 Beyer HG, "An Alternative Explanation for the Manner in which Genetic Algorithms Operate," Biosystems, vol. 41, pp. 1-15, 1997.   DOI
6 이상경, 고광은, 심귀보, "Harmony Search 알고리즘의 수렴성 개선에 관한 연구," 한국지능시스템학회 2011년도 춘계학술대회, 제21권, 1호, pp.31-34, 2011.
7 김종우, 김원배, 우효섭, "첨단 최적화 기술과 토목공학상의 응용," 대한토목학회지, 제55권, pp. 4-186, 2007.
8 Z.W. Geem and K.B. Sim, "Parameter-setting-free harmony search algorithm," Applied Mathematics and Computation, vol. 217, 2010.
9 M. G. H. Omran and M. Mahdavi, "Global-best harmony search," Applied Mathematics and Computation, vol. 198, 2005.
10 Holland J. H., "Adaptation in Natural and Artificial Systems," MC; University of Michigan Press, 1975.