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LP Solvable Models for Multiagent Fair Allocation problems

Julien Lesca
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Patrice Perny


This paper proposes several operational approaches for solving fair allocation problems in the context of multiagent optimization. These problems arise in various contexts such as assigning conference papers to referees or sharing of indivisible goods among agents. We present and discuss various social welfare functions that might be used to maximize the satisfaction of agents while maintaining a notion of fairness in the distribution. All these welfare functions are in fact non-linear, which precludes the use of classical min-cost max-flow algorithms for finding an optimal allocation. For each welfare function considered, we present a Mixed Integer Linear Programming formulation of the allocation problem that can be efficiently solved using standard solvers. The results of numerical tests we conducted on realistic cases are given at the end of the paper to confirm the practical feasibility of the proposed approaches.
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hal-01291467 , version 1 (21-03-2016)



Julien Lesca, Patrice Perny. LP Solvable Models for Multiagent Fair Allocation problems. European Conference on Artificial Intelligence, Aug 2010, Lisbon, Portugal. pp.393-398, ⟨10.3233/978-1-60750-606-5-393⟩. ⟨hal-01291467⟩
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