A modified cuckoo search using different search strategies
Abstract
Cuckoo search (CS) is one of the recent population-based algorithms used
for solving continuous optimization problems. The most known problem for
optimization techniques is balancing between exploration and exploitation. CS
uses two search strategies to updating the nest: local and global search. Although cuckoo search are adequate for the
exploration, it is not well enough the exploitation. Only one search equation
is used for local search, this equation remains incapable and causes some
deficiencies about the exploitation. To
enhance the ability of exploitation and to balance between global search and
local search, different search strategies were implemented in CS algorithm. The
proposed method was compared with basic CS on well-known unimodal and multimodal
benchmark functions. Experimental results show that the proposed method is more
successful than the basic CS in terms of solution quality.
Keywords
References
- [1] J. Kennedy, R. Eberhart, “Particle swarm optimization”, in: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, 1995, pp. 39–43.
- [2] D. Karaboga, “An idea based on honey bee swarm for numerical optimization”,Technical Report-TR06, Erciyes University, Engineering Faculty, Comput. Eng.Dep., 2005.
- [3] M. Dorigo, G.D. Caro, “Ant colony optimization: a new meta-heuristic”, in: Proceedings of the 1999 Congress on Evolutionary Computation, 1999, pp. 1470–1477.
- [4] X.-S. Yang, “Firefly algorithms for multimodal optimization”, in: 5th International Symposium SAGA, 2009, pp. 169–178.
- [5] X.-S. Yang, “A new metaheuristic bat-inspired algorithm”, in: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) (Eds. Cruz C., Gonzalez J., Krasnogor N., and Terraza G.), Springer, SCI 284, 65-74, 2010.
- [6] X.-S. Yang and S. Deb, “Cuckoo search via Le´vy flights”, in Proceedings of world congress on nature and biologically inspired computing IEEE Publications, 2009, pp. 210–214.
- [7] C. Cobos, H. Muñoz-Collazos, R. Urbano-Muñoz, M. Mendoza, E. León and E. Herrera-Viedma, “Clustering of web search results based on the cuckoo search algorithm and Balanced Bayesian Information Criterion”, Information Sciences, vol. 281, pp. 248–264, 2014.
- [8] T. T. Nguyen, D. N. Vo and T. T. Dao, “Cuckoo Search Algorithm Using Different Distributions for Short-Term Hydrothermal Scheduling with Cascaded Hydropower Plants”, in Proc. TENCON’14 , 2014, pp. 1-6.
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Authors
Hüseyin Haklı
SELCUK UNIV
Türkiye
Publication Date
December 26, 2016
Submission Date
December 1, 2016
Acceptance Date
December 1, 2016
Published in Issue
Year 2016 Volume: 4 Number: Special Issue-1