Global Optimization Method Based on Consensus Particle Swarm Optimization

Authors

Zhanwen Lu, 1. School of Electrical Engineering, University of Ji'nan, Ji'nan 250022, China; ;
Xingong Cheng, 1. School of Electrical Engineering, University of Ji'nan, Ji'nan 250022, China; ;2. Center of Intelligent System and Optimization Technology, University of Ji'nan-Global Optimal Big Data, Ji'nan 250022, China;
Yongfeng Zhang, 1. School of Electrical Engineering, University of Ji'nan, Ji'nan 250022, China; ;2. Center of Intelligent System and Optimization Technology, University of Ji'nan-Global Optimal Big Data, Ji'nan 250022, China;

Abstract

Abstract: According to the characteristics of particle swarm optimization (PSO) and efficient global optimization algorithm (EGO), a global black box optimization algorithm based on consensus particle swarm optimization and local surrogate model (CPSO-LSM) is proposed. The algorithm fixes the period of the PSO algorithm to group the particles and stops after the particles reach a consensus. The high-quality sub-regions around each group of particles are used as the modeling area of the surrogate model, and the high-quality optimal solution or global optimal solution is obtained by comparing the optimal values of each region. It can not only avoid the complex calculation of PSO, improve the speed and precision of establishing agent model, but also avoid falling into local optimum. By comparing the simulation results of other algorithms in standard test functions, CPSO-LSM has better convergence speed and solution accuracy.

Recommended Citation

Lu, Zhanwen; Cheng, Xingong; and Zhang, Yongfeng (2020) "Global Optimization Method Based on Consensus Particle Swarm Optimization," Journal of System Simulation: Vol. 32: Iss. 10, Article 11.
DOI: 10.16182/j.issn1004731x.joss.20-FZ0371
Available at: https://dc-china-simulation.researchcommons.org/journal/vol32/iss10/11

First Page

1936

Revised Date

2020-06-17

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-FZ0371

Last Page

1942

CLC

TP301.6

Recommended Citation

Lu Zhanwen, Cheng Xingong, Zhang Yongfeng. Global Optimization Method Based on Consensus Particle Swarm Optimization[J]. Journal of System Simulation, 2020, 32(10): 1936-1942.

Corresponding Author

Yongfeng Zhang,

DOI

10.16182/j.issn1004731x.joss.20-FZ0371