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Mathematical Problems in Engineering
Volume 2016, Article ID 4839763, 11 pages
http://dx.doi.org/10.1155/2016/4839763
Research Article

Cuckoo Search Algorithm with Hybrid Factor Using Dimensional Distance

1College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2College of Management, Fujian University of Traditional Chinese Medicine, Fuzhou 350002, China

Received 15 May 2016; Accepted 6 November 2016

Academic Editor: Salvatore Alfonzetti

Copyright © 2016 Yaohua Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper proposes a hybrid factor strategy for cuckoo search algorithm by combining constant factor and varied factor. The constant factor is used to the dimensions of each solution which are closer to the corresponding dimensions of the best solution, while the varied factor using a random or a chaotic sequence is utilized to farer dimensions. For each solution, the dimension whose distance to the corresponding one of the best solution is shorter than mean distance of all dimensional distances will be regarded as the closer one, otherwise as the farer one. A suit of 20 benchmark functions are employed to verify the performance of the proposed strategy, and the results show the improvement in effectiveness and efficiency of the hybridization.