A simple on-line bin-packing algorithm
Journal of the ACM (JACM)
Mathematica in action
Optimal time-critical scheduling via resource augmentation (extended abstract)
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Page replacement for general caching problems
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
On-line Packing and Covering Problems
Developments from a June 1996 seminar on Online algorithms: the state of the art
The Online Transportation Problem
ESA '95 Proceedings of the Third Annual European Symposium on Algorithms
Speed is as powerful as clairvoyance [scheduling problems]
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
On the Online Bin Packing Problem
ICALP '01 Proceedings of the 28th International Colloquium on Automata, Languages and Programming,
New Bounds for Variable-Sized and Resource Augmented Online Bin Packing
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Removable Online Knapsack Problems
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
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We study online bounded space bin packing in the resource augmentation model of competitive analysis. In this model, the online bounded space packing algorithm has to pack a list L of items in (0, 1) into a small number of bins of size b ≥ 1. Its performance is measured by comparing the produced packing against the optimal offline packing of the list L into bins of size 1. We present a complete solution to this problem: For every bin size b ≥ 1, we design online bounded space bin packing algorithms whose worst case ratio in this model comes arbitrarily close to a certain bound ρ(b). Moreover, we prove that no online bounded space algorithm can perform better than ρ(b) in the worst case.