Probabilistic construction of deterministic algorithms: approximating packing integer programs
Journal of Computer and System Sciences - 27th IEEE Conference on Foundations of Computer Science October 27-29, 1986
New results in the worst-case analysis for flow-shop scheduling
Discrete Applied Mathematics
On some geometric methods in scheduling theory: a survey
Discrete Applied Mathematics
Tight Bounds for Permutation Flow Shop Scheduling
Mathematics of Operations Research
Tight bounds for permutation flow shop scheduling
IPCO'08 Proceedings of the 13th international conference on Integer programming and combinatorial optimization
Permutation vs. non-permutation flow shop schedules
Operations Research Letters
Worst-case analysis of Dannenbring's algorithm for flow-shop scheduling
Operations Research Letters
Worst-case analysis of an approximation algorithm for flow-shop scheduling
Operations Research Letters
| Hi-index | 5.23 |
In the last 40 years, the permutation flow shop scheduling (PFS) problem with makespan minimization has been a central problem, known for its intractability, that has been well studied from both theoretical and practical aspects. The currently best performance ratio of a deterministic approximation algorithm for the PFS was recently presented by Nagarajan and Sviridenko, using a connection between the PFS and the longest increasing subsequence problem. In a different and independent way, this paper employs monotone subsequences in the approximation analysis techniques. To do this, an extension of the Erdos-Szekeres theorem to weighted monotone subsequences is presented. The result is a simple deterministic algorithm for the PFS with a similar approximation guarantee, but a much lower time complexity.