一种改进的粒子群优化算法

摘要

针对粒子群优化算法容易早熟、收敛精度不高的缺点，提出一种改进的粒子群优化算法，该算法在粒子陷入局部最优时，对聚集在种群全局最优位置附近的粒子进行变异。通过测试6个复杂函数的结果以及计算机配色模型求解实验，表明改进的粒子群优化算法优化效果远远优于2种典型的粒子群算法，新算法收敛精度高，收敛速度快，且有效预防了早熟现象。%In order to overcome the disadvantages of particle swarm optimization algorithm such as premature, bad searching ca-pability, a Modified Particle Swarm Optimization ( MPSO) algorithm was proposed. In this algorithm, when particles fall into the local extreme area, the particles, which gathered at the global optimal particle of the swarm, would have a mutation. Then test re-sults of six complex benchmark functions and computer color matching model indicate that MPSO is superior to other two classic PSOs, which has high convergence precision, fast convergence speed and prevents particle premature effectively.