Heterogeneous mayfly optimization algorithm

摘要

It appeared that with more updating ways, the optimization algorithms would perform better in optimization. In this paper, the heterogeneous mayfly optimization (HMO) algorithm was proposed. The individuals in the HMO swarms would have five ways to update their positions. Simulation experiments verified that the HMO algorithm would significantly increase the capabilities of the original mayfly optimization (MO) algorithm.