Research on Hybrid PSODE with Triple Populations Based on Multiple Differential Evolutionary Models

Regarding the complementarity of particle swarm optimization (PSO) and differential evolution (DE) and the complementarity of different differential evolutionary modes of DE, hybrid PSODE with three populations based on multiple differential evolutionary models is proposed. The algorithm effectively combines PSO and DE of two different evolutionary modes, improving local and global optimization ability dramatically. Hybrid PSODE with three populations, hybrid PSODE with two populations and hybrid DE with two populations are compared by 4 typical test functions, proving that hybrid PSODE with three populations has comprehensive superiority in global convergence properties and local search ability. Besides, among hybrid PSODE with three populations based on different differential evolutionary models, the algorithm with combination of rand and best evolutionary modes performs best and has perfect robustness and stability.