A Research of Simplified Particle Swarm Optimization Algorithm with Weight and Learning Factor

Xiaoyue Cao ； Xuxiu Zhang ； Yumeng Sun ； Zhenfu Kuai

《International Core Journal of Engineering》 5卷12期 (2019/11) Pp. 85-92

https://doi.org/10.6919/ICJE.201911_5(12).0012

摘要

In the view of the traditional particle swarm optimization algorithm is easy to get into the slow speed convergence and long search time when it solved the high-dimensional mathematical problems. In order to solve the problem that the independent adjustment of inertia weight and learning factor weakens the unity and intelligence of pso, the particle state factors is added to inertia weights and learning factors, A pso combining inertial weights and learning factors is presented.Based on the method of linear change of inertia weight, this algorithm adds the variable operator of inertia weight, which makes the inertia weight change dynamically with the iteration stage and aggregation of particles.And on the basis of simplifying particle swarm optimization, asynchronous transformation learning factor is added to make the position update formula dynamically updated according to the search situation of particles .Finally, the improved algorithm is compared with the existing algorithm on four test functions, and it is proved that the improved algorithm has obvious improvement on the optimization accuracy, iteration speed and convergence success rate.

關鍵字

particle swarm optimization ； adaptive ； Inertia weight ； simple particle swarm optimization

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