An improved lower bound for on-line bin packing algorithms
Information Processing Letters
Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
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)
On-line Packing and Covering Problems
Developments from a June 1996 seminar on Online algorithms: the state of the art
Strip packing with precedence constraints and strip packing with release times
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
A memetic algorithm and a parallel hyperheuristic island-based model for a 2D packing problem
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
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We study a new variant of on-line bin packing problem, in which each item ai is associated with a size ai and also a release time ri so that it must be placed at least ri above from the bottom of a bin. Items arrive in turn and must be assigned without any knowledge of subsequence items. The goal is to pack all items into unit-size bins using the minimum number of bins. We study the problem with all items have equal size. First, we show that the ANY FIT algorithm cannot be approximated within any constant. Then we present a best possible on-line algorithm with asymptotic competitive ratio of 2.