Better Approximation Guarantees for Job-Shop Scheduling

Authors:
Leslie Ann Goldberg;Mike Paterson;Aravind Srinivasan;Elizabeth Sweedyk
Affiliations:
-;-;-;-
Venue:
SIAM Journal on Discrete Mathematics
Year:
2001

Citing 0
Cited 8

Grouping Techniques for Scheduling Problems: Simpler and Faster

ESA '01 Proceedings of the 9th Annual European Symposium on Algorithms
Polynomial time approximation schemes for general multiprocessor job shop scheduling

Journal of Algorithms
Job shop scheduling with unit processing times

SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Job Shop Scheduling with Unit Processing Times

Mathematics of Operations Research
Improved Bounds for Flow Shop Scheduling

ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Hardness of Approximating Flow and Job Shop Scheduling Problems

Journal of the ACM (JACM)
Scheduling on unrelated machines under tree-like precedence constraints

APPROX'05/RANDOM'05 Proceedings of the 8th international workshop on Approximation, Randomization and Combinatorial Optimization Problems, and Proceedings of the 9th international conference on Randamization and Computation: algorithms and techniques
High-multiplicity cyclic job shop scheduling

Operations Research Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

Job-shop scheduling is a classical NP-hard problem. Shmoys, Stein, and Wein presented the first polynomial-time approximation algorithm for this problem that has a good (polylogarithmic) approximation guarantee. We improve the approximation guarantee of their work and present further improvements for some important NP-hard special cases of this problem (e.g., in the preemptive case where machines can suspend work on operations and later resume). We also present NC algorithms with improved approximation guarantees for some NP-hard special cases.