粒子群优化算法中惯性权重的研究进展

Research advances on inertia weight in particle swarm optimization

粒子群优化算法是根据鸟群觅食过程中的迁徙和群集模型而提出的用于解决优化问题的一类新兴的随机优化算法。惯性权重是粒子群算法中非常重要的参数,可以用来控制算法的开发和探索能力。简单介绍了标准粒子群优化算法的基本原理,全面综述了现有文献中对惯性权重的研究进展情况。

Particle Swarm Optimization （PSO） is a novel stochastic optimization algorithm based on the simulation of migration and the group model of bird flock in the process of their food-searching,and it can be used to solve optimization problems.Inertia weight is an important parameter in PSO,and it can control the algorithm＇s exploitation ability and exploration ability.This paper simply introduces the principle of PSO,and overviews the research advances in the inertia weight.