Implementation of a PTAS for Scheduling with Release Dates
ALENEX '01 Revised Papers from the Third International Workshop on Algorithm Engineering and Experimentation
Scheduling data transfers in a network and the set scheduling problem
Journal of Algorithms
Dynamic TCP acknowledgment in the LogP model
Journal of Algorithms
SPT is optimally competitive for uniprocessor flow
Information Processing Letters
An Experimental Study of LP-Based Approximation Algorithms for Scheduling Problems
INFORMS Journal on Computing
On the value of preemption in scheduling
APPROX'06/RANDOM'06 Proceedings of the 9th international conference on Approximation Algorithms for Combinatorial Optimization Problems, and 10th international conference on Randomization and Computation
A simpler proof of preemptive total flow time approximation on parallel machines
Efficient Approximation and Online Algorithms
Improving the preemptive bound for the one-machine dynamic total completion time scheduling problem
Operations Research Letters
Randomized algorithms for on-line scheduling problems: how low can't you go?
Operations Research Letters
Single machine batch scheduling with release times and delivery costs
Journal of Scheduling
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We consider the problem of scheduling n jobs that are released over time on a single machine in order to minimize the total flow time. This problem is well known to be NP-complete, and the best polynomial-time approximation algorithms constructed so far had (more or less trivial) worst-case performance guarantees of O(n). In this paper, we present one positive and one negative result on polynomial-time approximations for the minimum total flow time problem: The positive result is the first approximation algorithm with a sublinear worst-case performance guarantee of $O(\sqrt{n})$. This algorithm is based on resolving the preemptions of the corresponding optimum preemptive schedule. The performance guarantee of our approximation algorithm is not far from best possible, as our second, negative result demonstrates: Unless P=NP, no polynomial-time approximation algorithm for minimum total flow time can have a worst-case performance guarantee of $O(n^{1/2-\eps})$ for any $\eps0$.