Full characterization of core for nonlinear optimization games
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1866917210348322816 |
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| author | Du, Donglei Fang, Qizhi Liu, Bin Lu, Tianhang Wu, Chenchen |
| author_facet | Du, Donglei Fang, Qizhi Liu, Bin Lu, Tianhang Wu, Chenchen |
| contents | We fully characterize the core of a broad class of nonlinear games by identifying a suitable relaxation for inherent nonlinearity, directly generalizing the linear frameworks in the literature. This characterization significantly expands the scope of cooperative games that can be analyzed and contributes to the literature on games induced from optimization models. We apply these insights to not only establish connections with and provide new insights on classical models but also solve new games untamed in the existing literature, including combinatorial quadratic and ratio games such as portfolio, maximum cut, matching, and assortment games. These results are further extended to more general models and also the approximate core. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_13124 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Full characterization of core for nonlinear optimization games Du, Donglei Fang, Qizhi Liu, Bin Lu, Tianhang Wu, Chenchen Optimization and Control We fully characterize the core of a broad class of nonlinear games by identifying a suitable relaxation for inherent nonlinearity, directly generalizing the linear frameworks in the literature. This characterization significantly expands the scope of cooperative games that can be analyzed and contributes to the literature on games induced from optimization models. We apply these insights to not only establish connections with and provide new insights on classical models but also solve new games untamed in the existing literature, including combinatorial quadratic and ratio games such as portfolio, maximum cut, matching, and assortment games. These results are further extended to more general models and also the approximate core. |
| title | Full characterization of core for nonlinear optimization games |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2601.13124 |