Variable Metric Evolution Strategies for High-dimensional Multi-Objective Optimization
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913620977254400 |
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| author | Glasmachers, Tobias |
| author_facet | Glasmachers, Tobias |
| contents | We design a class of variable metric evolution strategies well suited for high-dimensional problems. We target problems with many variables, not (necessarily) with many objectives. The construction combines two independent developments: efficient algorithms for scaling covariance matrix adaptation to high dimensions, and evolution strategies for multi-objective optimization. In order to design a specific instance of the class we first develop a (1+1) version of the limited memory matrix adaptation evolution strategy and then use an established standard construction to turn a population thereof into a state-of-the-art multi-objective optimizer with indicator-based selection. The method compares favorably to adaptation of the full covariance matrix. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2412_15647 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Variable Metric Evolution Strategies for High-dimensional Multi-Objective Optimization Glasmachers, Tobias Neural and Evolutionary Computing We design a class of variable metric evolution strategies well suited for high-dimensional problems. We target problems with many variables, not (necessarily) with many objectives. The construction combines two independent developments: efficient algorithms for scaling covariance matrix adaptation to high dimensions, and evolution strategies for multi-objective optimization. In order to design a specific instance of the class we first develop a (1+1) version of the limited memory matrix adaptation evolution strategy and then use an established standard construction to turn a population thereof into a state-of-the-art multi-objective optimizer with indicator-based selection. The method compares favorably to adaptation of the full covariance matrix. |
| title | Variable Metric Evolution Strategies for High-dimensional Multi-Objective Optimization |
| topic | Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2412.15647 |