关键词: 粒子群, 多子群, 非线性约束优化

Abstract: This paper proposes an Improved Particle Swarm Optimization algorithm（IPSO）.IPSO adopts a new mutation operator and a new method that congregates some neighboring individuals to form multiple sub-populations in order to lead particles to explore new search space.Additionally，this algorithm incorporates a mechanism with a simple and easy penalty function to handle constraint.Thus，this algorithm has strong global exploratory capability and efficiency while being applied to solve nonlinear constrained optimization problems.Experimental results indicate that the IPSO is robust and efficient in solving nonlinear constrained optimization problems.

Key words: particle swarm, multiple sub-populations, nonlinear constrained optimization