Proportionally Fair Makespan Approximation

Fuente: arXiv
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Main Authors: Feldman, Michal, Garg, Jugal, Narayan, Vishnu V., Ponitka, Tomasz
Format: Preprint
Published: 2024
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author Feldman, Michal
Garg, Jugal
Narayan, Vishnu V.
Ponitka, Tomasz
author_facet Feldman, Michal
Garg, Jugal
Narayan, Vishnu V.
Ponitka, Tomasz
contents We study fair mechanisms for the classic job scheduling problem on unrelated machines with the objective of minimizing the makespan. This problem is equivalent to minimizing the egalitarian social cost in the fair division of chores. The two prevalent fairness notions in the fair division literature are envy-freeness and proportionality. Prior work has established that no envy-free mechanism can provide better than an $Ω(\log m/ \log \log m)$-approximation to the optimal makespan, where $m$ is the number of machines, even when payments to the machines are allowed. In strong contrast to this impossibility, our main result demonstrates that there exists a proportional mechanism (with payments) that achieves a $3/2$-approximation to the optimal makespan, and this ratio is tight. To prove this result, we provide a full characterization of allocation functions that can be made proportional with payments. Furthermore, we show that for instances with normalized costs, there exists a proportional mechanism that achieves the optimal makespan. We conclude with important directions for future research concerning other fairness notions, including relaxations of envy-freeness. Notably, we show that the technique leading to the impossibility result for envy-freeness does not extend to its relaxations.
format Preprint
id arxiv_https___arxiv_org_abs_2412_08572
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Proportionally Fair Makespan Approximation
Feldman, Michal
Garg, Jugal
Narayan, Vishnu V.
Ponitka, Tomasz
Computer Science and Game Theory
We study fair mechanisms for the classic job scheduling problem on unrelated machines with the objective of minimizing the makespan. This problem is equivalent to minimizing the egalitarian social cost in the fair division of chores. The two prevalent fairness notions in the fair division literature are envy-freeness and proportionality. Prior work has established that no envy-free mechanism can provide better than an $Ω(\log m/ \log \log m)$-approximation to the optimal makespan, where $m$ is the number of machines, even when payments to the machines are allowed. In strong contrast to this impossibility, our main result demonstrates that there exists a proportional mechanism (with payments) that achieves a $3/2$-approximation to the optimal makespan, and this ratio is tight. To prove this result, we provide a full characterization of allocation functions that can be made proportional with payments. Furthermore, we show that for instances with normalized costs, there exists a proportional mechanism that achieves the optimal makespan. We conclude with important directions for future research concerning other fairness notions, including relaxations of envy-freeness. Notably, we show that the technique leading to the impossibility result for envy-freeness does not extend to its relaxations.
title Proportionally Fair Makespan Approximation
topic Computer Science and Game Theory
url https://arxiv.org/abs/2412.08572