Computing Envy-Freeable Allocations with Limited Subsidies

Fair division has emerged as a very hot topic in EconCS research, and envy-freeness is among the most compelling fairness concepts. An allocation of indivisible items to agents is envy-free if no agent prefers the bundle of any other agent to his own in terms of value. As envy-freeness is rarely a feasible goal, there is a recent focus on relaxations of its definition. An approach in this direction is to complement allocations with payments (or subsidies) to the agents. A feasible goal then is to achieve envy-freeness in terms of the total value an agent gets from the allocation and the subsidies. We consider the natural optimization problem of computing allocations that are envy-freeable using the minimum amount of subsidies. As the problem is NP-hard, we focus on the design of approximation algorithms. On the positive side, we present an algorithm which, for a constant number of agents, approximates the minimum amount of subsidies within any required accuracy, at the expense of a graceful increase in the running time. On the negative side, we show that, for a superconstant number of agents, the problem of minimizing subsidies for envy-freeness is not only hard to compute exactly (as a folklore argument shows) but also, more importantly, hard to approximate.

Automated summary

The problem of minimizing subsidies for envy-freeness is a challenging task, with recent research focusing on designing approximation algorithms due to its NP-hard nature. While for a small number of agents, it is possible to approximate the minimum subsidy amount with a graceful increase in running time, for a superconstant number of agents, both exact computation and approximation are difficult.