Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Tight bounds for worst-case equilibria
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
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
An efficient approximation scheme for the one-dimensional bin-packing problem
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Convergence time to Nash equilibria
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
Nashification and the coordination ratio for a selfish routing game
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
On the packing of selfish items
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Worst-case analysis of the subset sum algorithm for bin packing
Operations Research Letters
The tight bound of first fit decreasing bin-packing algorithm is FFD(I) ≤ 11/9OPT(I) + 6/9
ESCAPE'07 Proceedings of the First international conference on Combinatorics, Algorithms, Probabilistic and Experimental Methodologies
Parametric Packing of Selfish Items and the Subset Sum Algorithm
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Theoretical Computer Science
Journal of Combinatorial Optimization
Non-cooperative games on multidimensional resource allocation
Future Generation Computer Systems
A note on a selfish bin packing problem
Journal of Global Optimization
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We study a bin packing game in which any item to be packed is handled by a selfish agent. Each agent aims at minimizing his sharing cost with the other items staying in the same bin, where the social cost is the number of bins used. We first show that computing a pure Nash equilibrium can be done in polynomial time. We then prove that the price of anarchy for the game is in between 1.6416 and 1.6575, improving the previous bounds.