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Autori principali: Du, Donglei, Fang, Qizhi, Liu, Bin, Lu, Tianhang, Wu, Chenchen
Natura: Preprint
Pubblicazione: 2026
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Accesso online:https://arxiv.org/abs/2601.13124
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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