Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems
Particle swarm optimization (PSO) is a widely recognized bio-inspired algorithm for systematically exploring solution spaces and iteratively iden-tifying optimal points. Through updating local and global best solutions, PSO effectively explores the search process, enabling the discovery of the most...
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| Format: | Article |
| Language: | English |
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Ferdowsi University of Mashhad
2025-03-01
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| Series: | Iranian Journal of Numerical Analysis and Optimization |
| Subjects: | |
| Online Access: | https://ijnao.um.ac.ir/article_45253_272249276bc5d2037bb43c74ec48c2da.pdf |
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| author | A. Falloun Y. Dursun A. Ait Madi |
| author_facet | A. Falloun Y. Dursun A. Ait Madi |
| author_sort | A. Falloun |
| collection | DOAJ |
| description | Particle swarm optimization (PSO) is a widely recognized bio-inspired algorithm for systematically exploring solution spaces and iteratively iden-tifying optimal points. Through updating local and global best solutions, PSO effectively explores the search process, enabling the discovery of the most advantageous outcomes. This study proposes a novel Smith chart-based particle swarm optimization to solve convex and nonconvex multi-objective engineering problems by representing complex plane values in a polar coordinate system. The main contribution of this paper lies in the utilization of the Smith chart’s impedance and admittance circles to dynamically update the location of each particle, thereby effectively deter-mining the local best particle. The proposed method is applied to three test functions with different behaviors, namely concave, convex, noncon-tinuous, and nonconvex, and performance parameters are examined. The simulation results show that the proposed strategy offers successful conver-gence performance for multi-objective optimization applications and meets performance expectations with a well-distributed solution set. |
| format | Article |
| id | doaj-art-5e2e26c74eb44e05b88e14617fad3e34 |
| institution | OA Journals |
| issn | 2423-6977 2423-6969 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Ferdowsi University of Mashhad |
| record_format | Article |
| series | Iranian Journal of Numerical Analysis and Optimization |
| spelling | doaj-art-5e2e26c74eb44e05b88e14617fad3e342025-08-20T02:13:39ZengFerdowsi University of MashhadIranian Journal of Numerical Analysis and Optimization2423-69772423-69692025-03-0115Issue 119721910.22067/ijnao.2024.86247.137145253Smith chart-based particle swarm optimization algorithm for multi-objective engineering problemsA. Falloun0Y. Dursun1A. Ait Madi2dvanced Systems Engineering Laboratory, National School of Applied Sciences, Keni-tra, Morocco.Electrical and electronic engineering, Marmara University,Istanbul, Türkiye.Advanced Systems Engineering Laboratory, National School of Applied Sciences, Ibn Tofail University, Kenitra, Morocco.Particle swarm optimization (PSO) is a widely recognized bio-inspired algorithm for systematically exploring solution spaces and iteratively iden-tifying optimal points. Through updating local and global best solutions, PSO effectively explores the search process, enabling the discovery of the most advantageous outcomes. This study proposes a novel Smith chart-based particle swarm optimization to solve convex and nonconvex multi-objective engineering problems by representing complex plane values in a polar coordinate system. The main contribution of this paper lies in the utilization of the Smith chart’s impedance and admittance circles to dynamically update the location of each particle, thereby effectively deter-mining the local best particle. The proposed method is applied to three test functions with different behaviors, namely concave, convex, noncon-tinuous, and nonconvex, and performance parameters are examined. The simulation results show that the proposed strategy offers successful conver-gence performance for multi-objective optimization applications and meets performance expectations with a well-distributed solution set.https://ijnao.um.ac.ir/article_45253_272249276bc5d2037bb43c74ec48c2da.pdfmulti-objective optimization (moo)particle swarm optimiza-tion (pso)meta-heuristic optimization |
| spellingShingle | A. Falloun Y. Dursun A. Ait Madi Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems Iranian Journal of Numerical Analysis and Optimization multi-objective optimization (moo) particle swarm optimiza-tion (pso) meta-heuristic optimization |
| title | Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems |
| title_full | Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems |
| title_fullStr | Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems |
| title_full_unstemmed | Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems |
| title_short | Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems |
| title_sort | smith chart based particle swarm optimization algorithm for multi objective engineering problems |
| topic | multi-objective optimization (moo) particle swarm optimiza-tion (pso) meta-heuristic optimization |
| url | https://ijnao.um.ac.ir/article_45253_272249276bc5d2037bb43c74ec48c2da.pdf |
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