An enhanced harmony search integrated with adaptive mutation strategy. (13th December 2022)

• Record Type: Journal Article
• Authors: Deng, Ying; Zhong, Yiwen; Wang, Lijin
• Is Part Of: International journal of computing science and mathematics. Volume 16:Number 2(2022)
• Page Start: 136
• Page End: 148
• Publication Date: 2022-12-13
• Subjects: harmony search -- differential mutation -- adaptive strategy -- current vector -- constructive algorithm; Mathematics -- Periodicals; Computer science -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.285
• Languages: English
• ISSNs: 1752-5055

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.