Theoretical Computer Science - Special issue on dynamic and on-line algorithms
Scheduling to minimize average completion time: off-line and on-line approximation algorithms
Mathematics of Operations Research
Approximation techniques for average completion time scheduling
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Single Machine Scheduling with Release Dates
SIAM Journal on Discrete Mathematics
Optimal On-Line Algorithms for Single-Machine Scheduling
Proceedings of the 5th International IPCO Conference on Integer Programming and Combinatorial Optimization
Developments from a June 1996 seminar on Online algorithms: the state of the art
Semi on-line algorithms for the partition problem
Operations Research Letters
Ordinal algorithms for parallel machine scheduling
Operations Research Letters
Semi-online scheduling with decreasing job sizes
Operations Research Letters
Journal of Global Optimization
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We consider the problem of scheduling jobs on-line on a single machine with the objective of minimizing total completion time. We assume that jobs arrive over time and that release dates are known in advance, but not the processing times. The most important result we are given in this paper is the competitive analysis of a new clairvoyant on-line algorithm for this scheduling problem. We are proving that this deterministic semi-online algorithm, called ST-α, is \sqrt3-competitive, which beats the existing lower bound for non-clairvoyant online algorithms.