Universally truthful mechanisms for scheduling

2026-09-11

AI Summary

研究了在n个不相关机器上调度m个作业的问题，证明了任何具有离散支持的概率分布的普遍真实随机机制的预期近似比下界，并提出了一种达到n/2+o(n)近似比的机制。

Abstract

We consider universally truthful randomized mechanisms for the problem of scheduling $m$ jobs on $n$ unrelated machines. We prove a lower bound on the expected approximation ratio of every such mechanism whose probability distribution has discrete support. We show that no universally truthful randomized mechanism in this class can achieve approximation ratio smaller than $n/12 - o(n)$ with respect to the optimal makespan. We match this, up to a constant factor, by a mechanism with approximation ratio $n/2 + o(n)$.

Problem

• universally truthful mechanisms
• scheduling
• approximation ratio
• unrelated machines

Innovation

• universally truthful mechanisms
• scheduling
• expected approximation ratio
• discrete support