A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems
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 escap...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2022-12-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-1178.pdf |
| _version_ | 1798005883913895936 |
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| author | Ying Sun Wanyuan Shi Yuelin Gao |
| author_facet | Ying Sun Wanyuan Shi Yuelin Gao |
| author_sort | Ying Sun |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T12:46:08Z |
| format | Article |
| id | doaj.art-2e06dce4eaaf4868ab8a5133283012f9 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-04-11T12:46:08Z |
| publishDate | 2022-12-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-2e06dce4eaaf4868ab8a5133283012f92022-12-22T04:23:21ZengPeerJ Inc.PeerJ Computer Science2376-59922022-12-018e117810.7717/peerj-cs.1178A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problemsYing Sun0Wanyuan Shi1Yuelin Gao2North Minzu University, Collaborative Innovation Center of Scientific Computing and Intelligent Processing in Ningxia, Yinchuan, Ningxia, ChinaNorth Minzu University, School of Mathematics and Information Sciences, Yinchuan, Ningxia, ChinaNorth Minzu University, Collaborative Innovation Center of Scientific Computing and Intelligent Processing in Ningxia, Yinchuan, Ningxia, ChinaTo 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.https://peerj.com/articles/cs-1178.pdfParticle swarm optimization algorithmConstrained optimization problemsDeb criterion |
| spellingShingle | Ying Sun Wanyuan Shi Yuelin Gao A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems PeerJ Computer Science Particle swarm optimization algorithm Constrained optimization problems Deb criterion |
| title | A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems |
| title_full | A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems |
| title_fullStr | A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems |
| title_full_unstemmed | A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems |
| title_short | A particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems |
| title_sort | particle swarm optimization algorithm based on an improved deb criterion for constrained optimization problems |
| topic | Particle swarm optimization algorithm Constrained optimization problems Deb criterion |
| url | https://peerj.com/articles/cs-1178.pdf |
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