Adoption of computer particle swarm optimization algorithm under thermodynamic motion mechanism

Qizhong Li, Yizheng Yue*, Zhongqi Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

In order to improve the stability and sensitivity of particle swarm optimization (PSO) algorithm and to solve the problem of premature convergence, in this re-search, a computer PSO algorithm based on thermodynamic motion mechanism is proposed based on the principle of thermodynamic motion mechanism. Firstly, the thermodynamic motion phenomenon, the diffusion law in kinematics and the standard PSO algorithm are introduced. Then, according to the basic idea of thermodynamic motion mechanism, the standardized PSO algorithm is optimized and its optimization process is introduced. Finally, the experimental results are analysed by setting the test function. The results show that among the five test functions, the computer PSO algorithm based on thermodynamic motion mecha-nism has a higher probability of jumping out of the local optimal solution. Its ro-bustness and stability are much better than standard PSO algorithms. The evolu-tion ability of the computer PSO algorithm based on thermodynamic motion mechanism is better than that of the standard PSO algorithm. The standard PSO algorithm is superior because it is based on thermodynamic motion mechanism. The research in this paper can provide good guidance for improving the perfor-mance of PSO algorithm.

Original languageEnglish
Pages (from-to)2707-2715
Number of pages9
JournalThermal Science
Volume24
DOIs
Publication statusPublished - 2020

Keywords

  • Convergence
  • PSO algorithm
  • Test functions
  • Thermodynamic motion mechanism

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