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@nomuramasahir0 [2] Ryoki Hamano, Masahiro Nomura, Shota Saito, Kento Uchida, and Shinichi Shirakawa. 2026. CatCMA with Margin for Single- and Multi-Objective Mixed-Variable Black-Box Optimization, arXiv:2504.07884. |
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LGTM! |
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I have implemented COMO-CatCMA with Margin (COMO-CatCMAwM), a multi-objective extension of CatCMA with Margin built on the Sofomore framework [1]. This implementation enables multi-objective optimization over mixed search spaces with any combination of continuous, integer, and categorical variables. The current implementation supports bi-objective optimization; support for three or more objectives will be added in future work.
At this stage, the related references and a full README section are still being prepared, so the detailed README update will be provided in a follow-up.
This PR also adds a small UHVI (uncrowded hypervolume improvement) evaluation utility in _uhvi_archiving.py. The implementation is intentionally minimal and is partially adapted from moarchiving for the 2D case; please refer to the code comments for attribution and implementation details.
[1] Cheikh Touré, Nikolaus Hansen, Anne Auger, and Dimo Brockhoff. 2019. Uncrowded hypervolume improvement: COMO-CMA-ES and the sofomore framework. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '19).