Open AccessThe improved mayfly optimization algorithm
Author(s) -
Zheng-Ming Gao,
Juan Zhao,
Su-Ruo Li,
Yurong Hu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1684/1/012077
Subject(s) - mayfly , particle swarm optimization , cartesian coordinate system , algorithm , mathematical optimization , multi swarm optimization , computer science , differential evolution , optimization algorithm , meta optimization , mathematics , geometry , botany , nymph , biology
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.