Bin packing game with a price of anarchy of $$\frac{3}{2}$$ 3 2
Q. Q. Nong (),
T. Sun,
T. C. E. Cheng and
Q. Z. Fang
Additional contact information
Q. Q. Nong: Ocean University of China
T. Sun: Ocean University of China
T. C. E. Cheng: The Hong Kong Polytechnic University
Q. Z. Fang: Ocean University of China
Journal of Combinatorial Optimization, 2018, vol. 35, issue 2, No 21, 632-640
Abstract:
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 $$\frac{3}{2}$$ 3 2 and prove that any feasible packing can converge to a Nash equilibrium in $$n^2-n$$ n 2 - n steps without increasing the social cost.
Keywords: Game; Nash equilibrium; Price of anarchy; Bin packing (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://link.springer.com/10.1007/s10878-017-0201-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:jcomop:v:35:y:2018:i:2:d:10.1007_s10878-017-0201-6
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10878
DOI: 10.1007/s10878-017-0201-6
Access Statistics for this article
Journal of Combinatorial Optimization is currently edited by Thai, My T.
More articles in Journal of Combinatorial Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().