关键词: 群体智能, 粒子群优化, 权重, 吸引子, 内嵌区域震荡搜索

Abstract: In order to solve the problem, which particle swarm optimization has low accuracy and slow speed in searching optimal, many scholars have proposed various methods which improve the optimization to make particle swarm algorithm more efficient. This paper presents an improved method by adjusting the global and individual optimal solution to form a new global attractor solution, optimizing the search for the optimal value of the particle populations in the solution space. Then embedds it into regional shock search embedded PSO（RSPSO）, the simulation results show that searching ability and the search accuracy of the improved particle swarm optimization has been further improved.

Key words: swarm intelligence, particle swarm optimization, weight, attractors, regional shock search embedded