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Research demonstrates new algorithms for stable matching in non-bipartite systems, indicating innovative optimality criteria.
Non-bipartite matching problems arise naturally in many multi-agent systems, yet they face a fundamental challenge absent from classical bipartite markets: even under strict preferences, stable matchings need not exist. This non-existence requires a careful combinatorial study of preference structures, and calls for the design of advanced algorithms when aiming for alternative fairness or relaxed stability guarantees in such settings. I study the structural origins of instability in non-bipartite preference systems, develop new optimality criteria inspired by both classical social choice theory and by real-world requirements, and design efficient algorithms for the computation of matchings satisfying such criteria if possible.
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Frederik Glitzner (2026) studied this question.
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