We consider the problem of maximizing the Nash social welfare when allocating a set G of indivisible goods to a set N of agents. We study instances, in which all agents have 2-value additive valuations: The value of every agent i ∈ N for every good j ∈ G is vij ∈ (p, q), for p, q ∈ N, p ≤ q. In this work, we design an algorithm to compute an optimal allocation in polynomial time if p divides q, i.e., when p = 1 and q ∈ N after appropriate scaling. The problem is NP-hard whenever p and q are coprime and p ≥ 3. In terms of approximation, we present positive and negative results for general p and q. We show that our algorithm obtains an approximation ratio of at most 1.0345. Moreover, we prove that the problem is APX-hard, with a lower bound of 1.000015 achieved at p/q = 4/5.

Maximizing Nash Social Welfare in 2-Value Instances

Varricchio G.;
2022-01-01

Abstract

We consider the problem of maximizing the Nash social welfare when allocating a set G of indivisible goods to a set N of agents. We study instances, in which all agents have 2-value additive valuations: The value of every agent i ∈ N for every good j ∈ G is vij ∈ (p, q), for p, q ∈ N, p ≤ q. In this work, we design an algorithm to compute an optimal allocation in polynomial time if p divides q, i.e., when p = 1 and q ∈ N after appropriate scaling. The problem is NP-hard whenever p and q are coprime and p ≥ 3. In terms of approximation, we present positive and negative results for general p and q. We show that our algorithm obtains an approximation ratio of at most 1.0345. Moreover, we prove that the problem is APX-hard, with a lower bound of 1.000015 achieved at p/q = 4/5.
2022
Game Theory And Economic Paradigms
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/358799
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