Name
Title | ||
|---|---|---|
Asymptotically optimal policy for stochastic job shop scheduling problem to minimize makespan. |
Abstract | ||
|---|---|---|
This paper studies the large-scale stochastic job shop scheduling problem with number of jobs, where the processing times of the same step are independently drawn from a known probability distribution, and the objective is to minimize the makespan. For the stochastic problem, we introduce the fluid relaxation of its deterministic counterpart, and define a fluid schedule for the fluid relaxation. By tracking the fluid schedule, a policy is proposed for the stochastic job shop scheduling problem. The expected value of the gap between the solution produced by the policy and the optimal solution is proved to be (1), which indicates the policy is asymptotically optimal in expectation. |
Year | DOI | Venue |
|---|---|---|
2018 | https://doi.org/10.1007/s10878-018-0294-6 | J. Comb. Optim. |
Keywords | Field | DocType |
Stochastic scheduling,Job shop,Fluid relaxation,Asymptotical optimality | Mathematical optimization,Job shop scheduling,Job shop scheduling problem,Job shop,Expected value,Probability distribution,Asymptotically optimal algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
36 | 1 | 1382-6905 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinwei Gu | 1 | 687 | 39.49 |
| Manzhan Gu | 2 | 36 | 4.99 |
| Xiwen Lu | 3 | 182 | 21.03 |
| Ying Zhang | 4 | 18 | 4.13 |