Title: An enhanced cuckoo search using dimension selection

Authors: Lijin Wang; Yihong Zhuang; Zhennan Chen; Yiwen Zhong

Addresses: College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China; Key Laboratory of Smart Agriculture and Forestry, Fujian Province University, Fuzhou, China; The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions, Wuyi University, Wuyishan Shi, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China; Key Laboratory of Smart Agriculture and Forestry, Fujian Province University, Fuzhou, China

Abstract: This paper proposes an enhanced cuckoo search algorithm using dimension selection. In the proposed strategy, the dimensional distance measure is used to select a part of dimensions of each solution to search for the new solution in two search components. The dimensions of each solution are selected when those dimensional distances are larger than the average distance of all dimensional distance. A suit of 20 benchmark functions are employed to verify the performance of the proposed algorithm, and the results show the improvement in effectiveness and efficiency of dimension selection.

Keywords: cuckoo search algorithm; dimension selection; dimensional distance; average distance; crossover operator.

DOI: 10.1504/IJICA.2019.100512

International Journal of Innovative Computing and Applications, 2019 Vol.10 No.1, pp.3 - 11

Received: 13 Jun 2018
Accepted: 28 Aug 2018
Published online: 29 Jun 2019 *

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