Title: An enhanced harmony search integrated with adaptive mutation strategy

Authors: Ying Deng; Yiwen Zhong; Lijin Wang

Addresses: College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China; Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 350002, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China; Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 350002, China ' College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 350002, China; Digital Fujian Tourism Big Data Institute, Wuyi University, Wuyishan, 354300, China

Abstract: Aiming at making improvements on solutions to function optimisation problems, an enhanced harmony search, called EHS, is proposed by hybridising differential mutation strategies. EHS employs differential mutation strategies after a solution generated by harmony search, then the solution is integrated into the differential mutation strategies as a target or current vector. Moreover, four differential mutation operators, including target-to-rand/1, target-to-rand/2, target-to-best/1 and target-to-best/2 are invoked adaptively in a random way. Extensive experiments on CEC2014 benchmark functions demonstrate EHS is effective and efficient with the combination of harmony search and the differential mutation strategies.

Keywords: harmony search; differential mutation; adaptive strategy; current vector; constructive algorithm.

DOI: 10.1504/IJCSM.2022.127806

International Journal of Computing Science and Mathematics, 2022 Vol.16 No.2, pp.136 - 148

Received: 03 Dec 2020
Accepted: 11 Feb 2021
Published online: 19 Dec 2022 *

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