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Erschienen in: Journal of Combinatorial Optimization 2/2018

09.11.2017

Bin packing game with a price of anarchy of \(\frac{3}{2}\)

verfasst von: Q. Q. Nong, T. Sun, T. C. E. Cheng, Q. Z. Fang

Erschienen in: Journal of Combinatorial Optimization | Ausgabe 2/2018

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Abstract

We consider the bin packing problem in the non-cooperative game setting. In the game there are a set of items with sizes between 0 and 1 and a number of bins each with a capacity of 1. Each item seeks to be packed in one of the bins so as to minimize its cost (payoff). The social cost is the number of bins used in the packing. Existing research has focused on three bin packing games with selfish items, namely the Unit game, the Proportional game, and the General Weight game, each of which uses a unique payoff rule. In this paper we propose a new bin packing game in which the payoff of an item is a function of its own size and the size of the maximum item in the same bin. We find that the new payoff rule induces the items to reach a better Nash equilibrium. We show that the price of anarchy of the new bin packing game is \(\frac{3}{2}\) and prove that any feasible packing can converge to a Nash equilibrium in \(n^2-n\) steps without increasing the social cost.

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Metadaten
Titel
Bin packing game with a price of anarchy of
verfasst von
Q. Q. Nong
T. Sun
T. C. E. Cheng
Q. Z. Fang
Publikationsdatum
09.11.2017
Verlag
Springer US
Erschienen in
Journal of Combinatorial Optimization / Ausgabe 2/2018
Print ISSN: 1382-6905
Elektronische ISSN: 1573-2886
DOI
https://doi.org/10.1007/s10878-017-0201-6

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