The Min Max Average Cycle Weight Problem

TL;DR

This paper introduces the Min Max Average Cycle Weight problem, a combinatorial optimization challenge related to fair redistribution in apartment rebuilding, highlighting its computational complexity and open questions.

Contribution

It formulates a novel optimization problem linking envy minimization to cycle weights and explores its computational complexity, especially with preexisting conditions.

Findings

Polynomial-time solvable in the clean slate case

Complexity increases with preexisting conditions

Open problem for general case solvability

Abstract

When an old apartment building is demolished and rebuilt, how can we fairly redistribute the new apartments to minimize envy among residents? We reduce this question to a combinatorial optimization problem called the *Min Max Average Cycle Weight* problem. In that problem we seek to assign objects to agents in a way that minimizes the maximum average weight of directed cycles in an associated envy graph. While this problem reduces to maximum-weight matching when starting from a clean slate (achieving polynomial-time solvability), we show that this is not the case when we account for preexisting conditions, such as residents' satisfaction with their original apartments. Whether the problem is polynomial-time solvable in the general case remains an intriguing open problem.