A scalable coevolutionary multi-objective particle swarm optimizer
Multi-Objective Particle Swarm Optimizers (MOPSOs) are easily trapped in local optima, cost more function evaluations and suffer from the curse of dimensionality. A scalable cooperative coevolution and ?-dominance based MOPSO (CEPSO) is proposed to address these issues. In CEPSO, Multi-objective Opt...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Springer
2010-11-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/2100.pdf |
| _version_ | 1818216370999918592 |
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| author | Xiangwei Zheng Hong Liu |
| author_facet | Xiangwei Zheng Hong Liu |
| author_sort | Xiangwei Zheng |
| collection | DOAJ |
| description | Multi-Objective Particle Swarm Optimizers (MOPSOs) are easily trapped in local optima, cost more function evaluations and suffer from the curse of dimensionality. A scalable cooperative coevolution and ?-dominance based MOPSO (CEPSO) is proposed to address these issues. In CEPSO, Multi-objective Optimization Problems (MOPs) are decomposed in terms of their decision variables and are optimized by cooperative coevolutionary subswarms, and a uniform distribution mutation operator is adopted to avoid premature convergence. All subswarms share an external archive based on ?-dominance, which is also used as a leader set. Collaborators are selected from the archive and used to construct context vectors in order to evaluate particles in a subswarm. CEPSO is tested on several classical MOP benchmark functions and experimental results show that CEPSO can readily escape from local optima and optimize both low and high dimensional problems, but the number of function evaluations only increases linearly with respect to the number of decision variables. Therefore, CEPSO is competitive in solving various MOPs. |
| first_indexed | 2024-12-12T06:50:54Z |
| format | Article |
| id | doaj.art-5a47dea84c234250a73a58e3f878eec4 |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-12-12T06:50:54Z |
| publishDate | 2010-11-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-5a47dea84c234250a73a58e3f878eec42022-12-22T00:34:04ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832010-11-013510.2991/ijcis.2010.3.5.8A scalable coevolutionary multi-objective particle swarm optimizerXiangwei ZhengHong LiuMulti-Objective Particle Swarm Optimizers (MOPSOs) are easily trapped in local optima, cost more function evaluations and suffer from the curse of dimensionality. A scalable cooperative coevolution and ?-dominance based MOPSO (CEPSO) is proposed to address these issues. In CEPSO, Multi-objective Optimization Problems (MOPs) are decomposed in terms of their decision variables and are optimized by cooperative coevolutionary subswarms, and a uniform distribution mutation operator is adopted to avoid premature convergence. All subswarms share an external archive based on ?-dominance, which is also used as a leader set. Collaborators are selected from the archive and used to construct context vectors in order to evaluate particles in a subswarm. CEPSO is tested on several classical MOP benchmark functions and experimental results show that CEPSO can readily escape from local optima and optimize both low and high dimensional problems, but the number of function evaluations only increases linearly with respect to the number of decision variables. Therefore, CEPSO is competitive in solving various MOPs.https://www.atlantis-press.com/article/2100.pdfMulti-objective optimization; Scalable; Cooperative coevolution; MOPSO |
| spellingShingle | Xiangwei Zheng Hong Liu A scalable coevolutionary multi-objective particle swarm optimizer International Journal of Computational Intelligence Systems Multi-objective optimization; Scalable; Cooperative coevolution; MOPSO |
| title | A scalable coevolutionary multi-objective particle swarm optimizer |
| title_full | A scalable coevolutionary multi-objective particle swarm optimizer |
| title_fullStr | A scalable coevolutionary multi-objective particle swarm optimizer |
| title_full_unstemmed | A scalable coevolutionary multi-objective particle swarm optimizer |
| title_short | A scalable coevolutionary multi-objective particle swarm optimizer |
| title_sort | scalable coevolutionary multi objective particle swarm optimizer |
| topic | Multi-objective optimization; Scalable; Cooperative coevolution; MOPSO |
| url | https://www.atlantis-press.com/article/2100.pdf |
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