A simple on-line bin-packing algorithm
Journal of the ACM (JACM)
Improved bounds for harmonic-based bin packing algorithms
Discrete Applied Mathematics - Special volume: combinatorics and theoretical computer science
An improved lower bound for on-line bin packing algorithms
Information Processing Letters
Analysis of Several Task-Scheduling Algorithms for a Model of Multiprogramming Computer Systems
Journal of the ACM (JACM)
New Algorithms for Bin Packing
Journal of the ACM (JACM)
On-line Packing and Covering Problems
Developments from a June 1996 seminar on Online algorithms: the state of the art
Online unit clustering: Variations on a theme
Theoretical Computer Science
Online interval coloring with packing constraints
Theoretical Computer Science
Approximation schemes for packing splittable items with cardinality constraints
WAOA'07 Proceedings of the 5th international conference on Approximation and online algorithms
Class constrained bin packing revisited
Theoretical Computer Science
AFPTAS Results for Common Variants of Bin Packing: A New Method for Handling the Small Items
SIAM Journal on Optimization
Online bin packing with cardinality constraints
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Online interval coloring with packing constraints
MFCS'05 Proceedings of the 30th international conference on Mathematical Foundations of Computer Science
Improved results for a memory allocation problem
WADS'07 Proceedings of the 10th international conference on Algorithms and Data Structures
Bin covering with cardinality constraints
Discrete Applied Mathematics
Hi-index | 0.05 |
The bin-packing problem asks for a packing of a list of items of sizes from (0,1] into the smallest possible number of bins having unit capacity. The k-item bin-packing problem additionally imposes the constraint that at most k items are allowed in one bin. We present two efficient on-line algorithms for this problem. We show that, for increasing values of k, the bound on the asymptotic worst-case performance ratio of the first algorithm tends towards 2 and that the second algorithm has a ratio of 2. Both algorithms considerably improve upon the best known result of an algorithm, which has an asymptotic bound of 2.7 on its ratio. Moreover, we improve known bounds for all values of k by presenting on-line algorithms for k = 2 and 3 with bounds on their ratios close to optimal.