Tractable Graph Structures in EFX Orientation
V\'aclav Bla\v{z}ej, Sushmita Gupta, M.S. Ramanujan, Peter Strulo

TL;DR
This paper investigates the computational complexity of EFX orientation in fair division, revealing that even slight deviations from bipartiteness lead to NP-hardness, and identifies graph structures that allow efficient solutions.
Contribution
It extends the understanding of EFX-orientation complexity by analyzing parameterized graph structures, showing NP-hardness under minimal deviations and providing tractability results for bounded treewidth graphs.
Findings
EFX orientation is NP-complete even near bipartite graphs.
Adding a non-binary value causes NP-hardness with minimal deviations.
Graphs with bounded treewidth allow linear-time solutions.
Abstract
Since its introduction, envy-freeness up to any good (EFX) has become a fundamental solution concept in fair division of indivisible goods. Its existence remains elusive -- even for four agents with additive utility functions, it is unknown whether an EFX allocation always exists. Unsurprisingly, restricted settings to delineate tractable and intractable cases have been explored. Christadolou, Fiat et al.[EC'23] introduced the notion of EFX-orientation, where the agents form the vertices of a graph and the items correspond to edges, and an agent values only the items that are incident to it. The goal is to allocate items to one of the adjacent agents while satisfying the EFX condition. Building on the work of Zeng and Mehta'24, which established a sharp complexity threshold based on the structure of the underlying graph -- polynomial-time solvability for bipartite graphs and…
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Taxonomy
TopicsConstraint Satisfaction and Optimization · Geographic Information Systems Studies · Data Management and Algorithms
