A self-adaptive multi-objective harmony search algorithm based on harmony memory variance

Xiangshan Dai, Xiaofang Yuan, Zhenjun Zhang

Abstract: Highlights•This paper aims to improve the performance of harmony search algorithm for solving multi-objective optimization problems.•Firstly, a novel self-adaptive mechanism has been proposed to improve performance of harmony search algorithm for solving multi-objective problems.•Secondly, the proposed algorithm is applied to solve many classical benchmark problems and it is also compared with other multi-objective evolutionary algorithms.•Thirdly, the proposed algorithm is applied to solve a practical engineering problem.•Fourthly, the impact of harmony memory size on the performance of the proposed algorithm is analyzed.