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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2506.13240 |
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| _version_ | 1866911007329222656 |
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| author | Viquerat, Jonathan |
| author_facet | Viquerat, Jonathan |
| contents | The optimization of mixed-variable problems remains a significant challenge. We propose an extension of the policy-based optimization method that handles mixed-variables problems in a natural way, through a simple policy combination. This is achieved by independently sampling from a multivariate normal distribution for the continuous domain, and from multiple categorical distributions for the discrete choices. Results demonstrate that the agent successfully yields high-quality solutions on a classical problem of electromagnetics, showcasing its robustness. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_13240 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Mixed-variable policy-based optimization Viquerat, Jonathan Optimization and Control Mathematical Physics The optimization of mixed-variable problems remains a significant challenge. We propose an extension of the policy-based optimization method that handles mixed-variables problems in a natural way, through a simple policy combination. This is achieved by independently sampling from a multivariate normal distribution for the continuous domain, and from multiple categorical distributions for the discrete choices. Results demonstrate that the agent successfully yields high-quality solutions on a classical problem of electromagnetics, showcasing its robustness. |
| title | Mixed-variable policy-based optimization |
| topic | Optimization and Control Mathematical Physics |
| url | https://arxiv.org/abs/2506.13240 |