The regrouping mayfly optimization algorithm
Juan Zhao, Zheng-Ming Gao · 2020 7th International Forum on Electrical Engineering and Automation (IFEEA) · 2020
The newly proposed mayfly optimization (MO) algorithm proved to be capable in optimizing both benchmark functions and engineering problems we met in our real world. Due to the original inspiration of the particle swarm optimization (PSO) algorithm, the MO algorithm would be also stagnated during iterations. In this paper, the regrouping method was introduced to reduce the stagnation for individuals in the MO algorithm. Simulation experiments would be carried out and results confirmed that the regrouping MO algorithm could reduce the stagnation for the MO algorithm in optimizing multimodal benchmark functions.