Non-Dominated Sorting Bidirectional Differential Coevolution
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866909365041102848 |
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| author | Mendes, Cicero S. R. Araújo, Aluizio F. R. Farias, Lucas R. C. |
| author_facet | Mendes, Cicero S. R. Araújo, Aluizio F. R. Farias, Lucas R. C. |
| contents | Constrained multiobjective optimization problems (CMOPs) are commonly found in real-world applications. CMOP is a complex problem that needs to satisfy a set of equality or inequality constraints. This paper proposes a variant of the bidirectional coevolution algorithm (BiCo) with differential evolution (DE). The novelties in the model include the DE differential mutation and crossover operators as the main search engine and a non-dominated sorting selection scheme. Experimental results on two benchmark test suites and eight real-world CMOPs suggested that the proposed model reached better overall performance than the original model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_19439 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Non-Dominated Sorting Bidirectional Differential Coevolution Mendes, Cicero S. R. Araújo, Aluizio F. R. Farias, Lucas R. C. Neural and Evolutionary Computing Constrained multiobjective optimization problems (CMOPs) are commonly found in real-world applications. CMOP is a complex problem that needs to satisfy a set of equality or inequality constraints. This paper proposes a variant of the bidirectional coevolution algorithm (BiCo) with differential evolution (DE). The novelties in the model include the DE differential mutation and crossover operators as the main search engine and a non-dominated sorting selection scheme. Experimental results on two benchmark test suites and eight real-world CMOPs suggested that the proposed model reached better overall performance than the original model. |
| title | Non-Dominated Sorting Bidirectional Differential Coevolution |
| topic | Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2410.19439 |