Improved Cuckoo Search Algorithm for Global Optimization

	Improved Cuckoo Search Algorithm for Global Optimization
International Journal of Communications and Information Technology
مقاله 7، دوره 1، شماره 1، اسفند 2011، صفحه 31-44 اصل مقاله (173.9 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22111/cit.2011.91
نویسندگان
E. Valian؛ S. Mohanna؛ S. Tavakoli
University of Sistan and Baluchestan
چکیده
The cuckoo search algorithm is a recently developed meta-heuristic optimization algorithm, which is suitable for solving optimization problems. To enhance the accuracy and convergence rate of this algorithm, an improved cuckoo search algorithm is proposed in this paper. Normally, the parameters of the cuckoo search are kept constant. This may lead to decreasing the efficiency of the algorithm. To cope with this issue, a proper strategy for tuning the cuckoo search parameters is presented. Considering several well-known benchmark problems, numerical studies reveal that the proposed algorithm can find better solutions in comparison with the solutions obtained by the cuckoo search. Therefore, it is anticipated that the improved cuckoo search algorithm can successfully be applied to a wide range of optimization problems.
کلیدواژه‌ها
Cuckoo search algorithm؛ global optimization؛ Lévy flight؛ Meta-heuristic؛ tuning

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