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Algorithms for Competitive Division of Chores

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arxiv 1907.01766 v2 pith:RFCWJMWV submitted 2019-07-03 cs.GT cs.DSecon.TH

classification cs.GTcs.DSecon.TH
keywords competitivechoresruleallocationsgoodsparetoagentscase
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We study the problem of allocating divisible bads (chores) among multiple agents with additive utilities when monetary transfers are not allowed. The competitive rule is known for its remarkable fairness and efficiency properties in the case of goods. This rule was extended to chores in prior work by Bogomolnaia, Moulin, Sandomirskiy, and Yanovskaya (2017). The rule produces Pareto optimal and envy-free allocations for both goods and chores. In the case of goods, the outcome of the competitive rule can be easily computed. Competitive allocations solve the Eisenberg-Gale convex program; hence the outcome is unique and can be approximately found by standard gradient methods. An exact algorithm that runs in polynomial time in the number of agents and goods was given by Orlin (2010). In the case of chores, the competitive rule does not solve any convex optimization problem; instead, competitive allocations correspond to local minima, local maxima, and saddle points of the Nash social welfare on the Pareto frontier of the set of feasible utilities. The Pareto frontier may contain many such points; consequently, the competitive rule's outcome is no longer unique. In this paper, we show that all the outcomes of the competitive rule for chores can be computed in strongly polynomial time if either the number of agents or the number of chores is fixed. The approach is based on a combination of three ideas: all consumption graphs of Pareto optimal allocations can be listed in polynomial time; for a given consumption graph, a candidate for a competitive utility profile can be constructed via an explicit formula; each candidate can be checked for competitiveness, and the allocation can be reconstructed using a maximum flow computation. Our algorithm gives an approximately-fair allocation of indivisible chores by the rounding technique of Barman and Krishnamurthy (2018).

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. To EFX OR to MMS, That is the Question

    cs.GT 2026-08 conditional novelty 7.0 of 10

    EFX∨MMS allocations can fail for three agents with submodular goods (8 items) or chores (7 items), but always exist for additive mixed items with at most three valuation types when one type is a singleton.

  2. A polynomial-time algorithm for computing a Pareto optimal and almost proportional allocation

    cs.GT 2019-09 conditional novelty 7.0 of 10

    For mixed goods and chores, a weighted Pareto-optimal allocation that is proportional up to one item always exists and is computable in strongly polynomial time.

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