Approximating Nash Social Welfare under Binary XOS and Binary Subadditive Valuations
Siddharth Barman, Paritosh Verma

TL;DR
This paper presents algorithms and hardness results for approximating Nash social welfare in allocating indivisible goods with binary valuation functions, focusing on binary XOS and subadditive valuations.
Contribution
It introduces a polynomial-time constant-factor approximation algorithm for binary XOS valuations and proves exponential query complexity for subadditive valuations, highlighting a separation between these classes.
Findings
Constant-factor approximation for binary XOS valuations
NP-hardness of maximizing Nash social welfare under binary XOS
Exponential query complexity for binary subadditive valuations
Abstract
We study the problem of allocating indivisible goods among agents in a fair and economically efficient manner. In this context, the Nash social welfare-defined as the geometric mean of agents' valuations for their assigned bundles-stands as a fundamental measure that quantifies the extent of fairness of an allocation. Focusing on instances in which the agents' valuations have binary marginals, we develop essentially tight results for (approximately) maximizing Nash social welfare under two of the most general classes of complement-free valuations, i.e., under binary XOS and binary subadditive valuations. For binary XOS valuations, we develop a polynomial-time algorithm that finds a constant-factor (specifically ) approximation for the optimal Nash social welfare, in the standard value-oracle model. The allocations computed by our algorithm also achieve constant-factor…
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