A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems

Ying Sun; Wanyuan Shi; Yuelin Gao

doi:10.7717/peerj-cs.1178

A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems

PeerJ Comput Sci. 2022 Dec 12:8:e1178. doi: 10.7717/peerj-cs.1178. eCollection 2022.

Authors

Ying Sun^{1

2}, Wanyuan Shi², Yuelin Gao^{1

2}

Affiliations

¹ North Minzu University, Collaborative Innovation Center of Scientific Computing and Intelligent Processing in Ningxia, Yinchuan, Ningxia, China.
² North Minzu University, School of Mathematics and Information Sciences, Yinchuan, Ningxia, China.

Abstract

To solve the nonlinear constrained optimization problem, a particle swarm optimization algorithm based on the improved Deb criterion (CPSO) is proposed. Based on the Deb criterion, the algorithm retains the information of 'excellent' infeasible solutions. The algorithm uses this information to escape from the local best solution and quickly converge to the global best solution. Additionally, to further improve the global search ability of the algorithm, the DE strategy is used to optimize the personal best position of the particle, which speeds up the convergence speed of the algorithm. The performance of our method was tested on 24 benchmark problems from IEEE CEC2006 and three real-world constraint optimization problems from CEC2020. The simulation results show that the CPSO algorithm is effective.

Keywords: Constrained optimization problems; Deb criterion; Particle swarm optimization algorithm.

Grants and funding

This research was funded by the Natural Science Foundation of NingXia Hui Autonomous Region (2021AAC03185), the Research Startup Foundation of North Minzu University (2020KYQD23), the First-Class Disciplines Foundation of NingXia (Grant No. NXYLXK2017B09) and the Major Project of North Minzu University (2019MS003). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.