[1]Lin Yaohua,Wang Li Jin.Elite Opposition-based Learning Based Simplex Crossover Cuckoo Search Algorithm[J].Journal of Zhengzhou University (Engineering Science),2017,38(06):33-38.[doi:10.13705/j.issn.1671-6833.2017.06.033]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
38
Number of periods:
2017 06
Page number:
33-38
Column:
Public date:
2017-11-20
- Title:
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Elite Opposition-based Learning Based Simplex Crossover Cuckoo Search Algorithm
- Author(s):
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Lin Yaohua; Wang Li Jin
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School of Computer and Information, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002
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- Keywords:
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cuckoo search algorithm; simplex crossover; opposite learning; chaotic maps
- CLC:
-
-
- DOI:
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10.13705/j.issn.1671-6833.2017.06.033
- Abstract:
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Cuckoo search algorithm iteratively uses Lévy Flights random walk and Biased random walk to search for new individuals. In this paper, an enhanced cuckoo search was proposed, which employed elite opposition-based learning, simplex crossover and parameter control for the fraction probablity. The elite opposition-based learning strategy was used to avoid the new individuals being homogeneous in the Lévy Flights random walk. The simplex crossover strategy was ulilized to reduce the inefficience of Biased random walk. The chaotic map was used to adaptivrly adjust the parameter pa to balance the exploration and the exploitation. The results of experiment showed the proposed strategies were overall effective, and make a great improvement on the performance of solution and convergence.