Approximation algorithms for scheduling unrelated parallel machines
Mathematical Programming: Series A and B
An approximation algorithm for max-min fair allocation of indivisible goods
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
SAGT'10 Proceedings of the Third international conference on Algorithmic game theory
A matroid approach to the worst case allocation of indivisible goods
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We study a fair division problem, where a set of indivisible goods is to be allocated to a set of n agents. In the continuous case, where goods are infinitely divisible, it is well known that proportional allocations always exist, i.e., allocations where every agent receives a bundle of goods worth to him at least $\frac{1}{n}$ . With indivisible goods however, this is not the case and one would like to find worst case guarantees on the value that every agent can have. We focus on algorithmic and mechanism design aspects of this problem. An explicit lower bound was identified by Hill [5], depending on n and the maximum value of any agent for a single good, such that for any instance, there exists an allocation that provides at least this guarantee to every agent. The proof however did not imply an efficient algorithm for finding such allocations. Following upon the work of [5], we first provide a slight strengthening of the guarantee we can make for every agent, as well as a polynomial time algorithm for computing such allocations. We then move to the design of truthful mechanisms. For deterministic mechanisms, we obtain a negative result showing that a truthful $\frac{2}{3}$ -approximation of these guarantees is impossible. We complement this by exhibiting a simple truthful algorithm that can achieve a constant approximation when the number of goods is bounded. Regarding randomized mechanisms, we also provide a negative result, under the restrictions that they are Pareto-efficient and satisfy certain symmetry requirements.