Title: A comparison of different transfer functions for binary version of grey wolf optimiser

Authors: Shuqin Wang; Gang Hua; Guosheng Hao; Chunli Xie

Addresses: School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China; School of Computer Science and Technology, Jiangsu Normal University, Xuzhou, Jiangsu, 221116, China ' School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China ' School of Computer Science and Technology, Jiangsu Normal University, Xuzhou, Jiangsu, 221116, China ' School of Computer Science and Technology, Jiangsu Normal University, Xuzhou, Jiangsu, 221116, China

Abstract: Grey Wolf Optimiser (GWO) is the recently proposed meta-heuristic algorithm inspired by grey wolves. The original version of GWO has been proposed to solve problems in continuous search spaces. However, there are many optimisation problems in discrete binary search spaces such as feature selection and dimensionality reduction. We applied eight transfer functions in our BGWO and compared their performance. The test functions whose minimum points are gotten at 0 are selected as bench functions but also those functions their minimum value are gotten at 1.

Keywords: grey wolf optimiser; binary optimisation; transfer function; test functions.

DOI: 10.1504/IJWMC.2017.089313

International Journal of Wireless and Mobile Computing, 2017 Vol.13 No.4, pp.261 - 269

Received: 11 Mar 2017
Accepted: 01 May 2017
Published online: 17 Jan 2018 *

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