Best Cost-Sharing Rule Design for Selfish Bin Packing

TL;DR

This paper introduces a new cost-sharing rule for selfish bin packing that achieves the optimal price of anarchy of 4/3, guarantees Nash equilibria, and improves stability and efficiency in the game.

Contribution

It proposes a simple, optimal cost-sharing rule with a PoA of 4/3, ensuring Nash equilibria and a PoS of 1, and connects to bin packing algorithms like BFD for stable solutions.

Findings

New cost-sharing rule achieves PoA of 4/3.

BFD algorithm produces strong equilibrium with 11/9 approximation.

Extended framework designs mechanisms with PoS=1 and PoA=4/3.

Abstract

In selfish bin packing, each item is regarded as a selfish player, who aims to minimize the cost-share by choosing a bin it can fit in. To have a least number of bins used, cost-sharing rules play an important role. The currently best known cost sharing rule has a \emph{price of anarchy} ($PoA$) larger than 1.45, while a general lower bound 4/3 on $PoA$ applies to any cost-sharing rule under which no items have the incentive to move unilaterally to an empty bin. In this paper, we propose a novel and simple rule with a $PoA$ matching the lower bound of $4/3$, thus completely resolving this game. The new rule always admits a Nash equilibrium and its \emph{price of stability} ($PoS$) is one. Furthermore, the well-known bin packing algorithm $BFD$ (Best-Fit Decreasing) is shown to achieve a strong equilibrium, implying that a stable packing with an asymptotic approximation ratio of $11/9$ can be produced in polynomial time. As an extension of the designing framework, we further study a variant of the selfish scheduling game, and design a best coordination mechanism achieving $PoS=1$ and $PoA=4/3$ as well.