The improved mayfly optimization algorithm
Zheng-Ming Gao, Juan Zhao, Su-Ruo Li, Yurong Hu
Abstract
Abstract The mayfly optimization (MO) algorithm was proposed with a better hybridization of the particle swarm optimization (PSO) and the differential evolution (DE) algorithms. The velocity would be relevant to the Cartesian distance among the relevant individuals. In this paper, a reasonable revision for the velocity updating equations was proposed based on the idea of moving towards each other as capable as they can. Simulation results proved that the improved MO algorithm would perform better than the original one.
Topics & Concepts
MayflyParticle swarm optimizationCartesian coordinate systemAlgorithmMathematical optimizationMulti-swarm optimizationComputer scienceDifferential evolutionOptimization algorithmMeta-optimizationMathematicsGeometryNymphBiologyBotanyMetaheuristic Optimization Algorithms ResearchAdvanced Multi-Objective Optimization AlgorithmsEvolutionary Algorithms and Applications