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arXiv · 1810.04331

Assignment Mechanisms under Distributional Constraints

Itai Ashlagi·Amin Saberi·Ali Shameli
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Abstract

We study the assignment problem of objects to agents with heterogeneous preferences under distributional constraints. Each agent is associated with a publicly known type and has a private ordinal ranking over objects. We are interested in assigning as many agents as possible. Our first contribution is a generalization of the well-known and widely used serial dictatorship. Our mechanism maintains several desirable properties of serial dictatorship, including strategyproofness, Pareto efficiency, and computational tractability while satisfying the distributional constraints with a small error. We also propose a generalization of the probabilistic serial algorithm, which finds an ordinally efficient and envy-free assignment, and also satisfies the distributional constraints with a small error. We show, however, that no ordinally efficient and envy-free mechanism is also weakly strategyproof. Both of our algorithms assign at least the same number of students as the optimum fractional assignment.

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Itai Ashlagi, Amin Saberi, Ali Shameli. 2018-10-10. Assignment Mechanisms under Distributional Constraints. https://arxiv.org/abs/1810.04331

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