A simple on-line bin-packing algorithm
Journal of the ACM (JACM)
A game theoretic framework for bandwidth allocation and pricing in broadband networks
IEEE/ACM Transactions on Networking (TON)
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Algorithms, games, and the internet
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
The Structure and Complexity of Nash Equilibria for a Selfish Routing Game
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Near-optimal network design with selfish agents
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Optimization problems in congestion control
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Designing Networks for Selfish Users is Hard
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
The Price of Stability for Network Design with Fair Cost Allocation
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
The effect of collusion in congestion games
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Tight bounds for worst-case equilibria
ACM Transactions on Algorithms (TALG)
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Bounds on multiprocessing anomalies and related packing algorithms
AFIPS '72 (Spring) Proceedings of the May 16-18, 1972, spring joint computer conference
Strong and correlated strong equilibria in monotone congestion games
WINE'06 Proceedings of the Second international conference on Internet and Network Economics
Atomic congestion games among coalitions
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part I
Strong price of anarchy for machine load balancing
ICALP'07 Proceedings of the 34th international conference on Automata, Languages and Programming
Parametric Packing of Selfish Items and the Subset Sum Algorithm
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Non-cooperative games on multidimensional resource allocation
Future Generation Computer Systems
Hi-index | 0.00 |
Following recent interest in the study of computer science problems in a game theoretic setting, we consider the well known bin packing problem where the items are controlled by selfish agents. Each agent is charged with a cost according to the fraction of the used bin space its item requires. That is, the cost of the bin is split among the agents, proportionally to their sizes. Thus, the selfish agents prefer their items to be packed in a bin that is as full as possible. The social goal is to minimize the number of the bins used. The social cost in this case is therefore the number of bins used in the packing.A pure Nash equilibrium is a packing where no agent can obtain a smaller cost by unilaterally moving his item to a different bin, while other items remain in their original positions. A Strong Nash equilibrium is a packing where there exists no subset of agents, all agents in which can profit from jointly moving their items to different bins. We say that all agents in a subset profit from moving their items to different bins if all of them have a strictly smaller cost as a result of moving, while the other items remain in their positions.We measure the quality of the equilibria using the standard measures PoAand PoSthat are defined as the worst case worst/best asymptotic ratio between the social cost of a (pure) Nash equilibrium and the cost of an optimal packing, respectively. We also consider the recently introduced measures SPoAand SPoS, that are defined similarly to the PoAand the PoS, but consider only Strong Nash equilibria.We give nearly tight lower and upper bounds of 1.6416 and 1.6428, respectively, on the PoAof the bin packing game, improving upon previous result by Bilò, and establish the fact that PoS= 1. We show that the bin packing game admits a Strong Nash equilibrium, and that SPoA=SPoS. We prove that this value is equal to the approximation ratio of a natural greedy algorithm for bin packing.