A simple on-line bin-packing algorithm
Journal of the ACM (JACM)
Parametric lower bound for on-line bin-packing
SIAM Journal on Algebraic and Discrete Methods
On-line bin packing in linear time
Journal of Algorithms
An improved lower bound for on-line bin packing algorithms
Information Processing Letters
Improved space for bounded-space, on-line bin-packing
SIAM Journal on Discrete Mathematics
A fundamental restriction on fully dynamic maintenance of bin packing
Information Processing Letters
Fully Dynamic Algorithms for Bin Packing: Being (Mostly) Myopic Helps
SIAM Journal on Computing
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Online bin packing with lookahead
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Page replacement for general caching problems
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Speed is as powerful as clairvoyance
Journal of the ACM (JACM)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
On the online bin packing problem
Journal of the ACM (JACM)
Algorithms for the Relaxed Online Bin-Packing Model
SIAM Journal on Computing
Resource augmentation for online bounded space bin packing
Journal of Algorithms
Worst-case analysis of memory allocation algorithms
STOC '72 Proceedings of the fourth annual ACM symposium on Theory of computing
Paging with connections: FIFO strikes again
Theoretical Computer Science
Fast algorithms for bin packing
Journal of Computer and System Sciences
Online bin packing with resource augmentation
WAOA'04 Proceedings of the Second international conference on Approximation and Online Algorithms
Discrete Optimization
Hi-index | 0.04 |
We study on-line bounded space bin-packing in the resource augmentation model of competitive analysis. In this model, the on-line bounded space packing algorithm has to pack a list L of items with sizes in (0, 1], into a minimum number of bins of size b, b=1. A bounded space algorithm has the property that it only has a constant number of active bins available to accept items at any point during processing. The performance of the algorithm is measured by comparing the produced packing with an optimal offline packing of the list L into bins of size 1. The competitive ratio then becomes a function of the on-line bin size b. Csirik and Woeginger studied this problem in [J. Csirik, G.J. Woeginger, Resource augmentation for online bounded space bin packing, Journal of Algorithms 44(2) (2002) 308-320] and proved that no on-line bounded space algorithm can perform better than a certain bound @r(b) in the worst case. We relax the on-line condition by allowing a complete repacking within the active bins, and show that the same lower bound holds for this problem as well, and repacking may only allow one to obtain the exact best possible competitive ratio of @r(b) having a constant number of active bins, instead of achieving this bound in the limit. We design a polynomial time on-line algorithm that uses three active bins and achieves the exact best possible competitive ratio @r(b) for the given problem.