Simplified Particle Swarm Optimization Algorithm Based on Improved Inertia Weight
GAO Wei
PING Huan
ZHANG Chenggang
JIANG Jingqing
Abstract：For the shortcomings of the traditional particle swarm optimization algorithm,which is easy to fall into local extreme,a new algorithm based on the simplified particle swarm optimization algorithm is proposed.Firstly,it removes the speed term,so it makes the algorithm simple.And then it mproves the dis-placement term.Finally it improves the inertia weight.Six classical functions are used to compare the tradi-tional particle swarm optimization algorithm,the simplified particle swarm optimization algorithm and the improved algorithm proposed in this paper.The experimental results show that the performance of the im-proved particle swarm optimization is better than the other two algorithms.
Keywords：velocity terminertia weightclassical functions
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 11-15 )