关键词: 粒子群优化算法, 三黑洞系统捕获, 多维随机干扰, 协调因子, 早熟扰动

Abstract:

Inspired by astrology and botany, Particle Swarm Optimization algorithm integrated with Multiple-Strategies（MSPSO） is proposed to improve the shortcoming of Particle Swarm Optimization（PSO） algorithm which is prone to local optimization. With the introduction of three-black-hole-system capture strategy and multiple-dimensional random interference strategy, the algorithm has enhanced global exploration ability with local exploitation capacity. And the algorithm transforms from global exploration to local exploitation through coordination coefficient, convergence speed is improved. At the same time, premature disturbance strategy is adopted to reduce the possibility of the algorithm falling into local optimization. Nine benchmark functions are used to compare the performance of the algorithm with other five algorithms. The simulation results show that MSPSO algorithm has the advantages of better optimization ability under the same iteration and faster convergence speed under the given accuracy.

Key words: Particle Swarm Optimization（PSO） algorithm, three-black-hole-system capture, multiple-dimensional random interference, coordination coefficient, premature disturbance