New Particle Swarm Optimisation Algorithm with H′enon Chaotic Map Structure

A new Particle swarm optimisation (PSO) algorithm based on the H′enon chaotic map (hereafter HCPSO algorithm) is presented in this paper to deal with the premature convergence problem of the traditional PSO algorithm. The HCPSO algorithm changes the structure of the traditional PSO algorithm and deviates from the structures of conventional hybrid algorithms that merely introduce chaotic searching into PSO. Based on the con-vergence condition of PSO, the HCPSO algorithm can im-prove solution precision and increase the convergence rate by combing using the targeting technique of chaotic map-ping. For validation, fourteen benchmark functions were used to compare the proposed algorithm with six other hy-brid PSO algorithms. The experimental results indicated that the HCPSO algorithm is superior to the other algo-rithms in terms of convergence speed and solution accu-racy.