Name
Title | ||
|---|---|---|
A scenario generation-based lower bounding approach for stochastic scheduling problems. |
Abstract | ||
|---|---|---|
In this paper, we investigate scenario generation methods to establish lower bounds on the optimal objective value for stochastic scheduling problems that contain random parameters with continuous distributions. In contrast to the Sample Average Approximation (SAA) approach, which yields probabilistic bound values, we use an alternative bounding method that relies on the ideas of discrete bounding and recursive stratified sampling. Theoretical support is provided for deriving exact lower bounds for both expectation and conditional value-at-risk objectives. We illustrate the use of our method on the single machine total weighted tardiness problem. The results of our numerical investigation demonstrate good properties of our bounding method, compared with the SAA method and an earlier discrete bounding method. Journal of the Operational Research Society (2012) 63, 1410-1420. doi: 10.1057/jors.2011.150 Published online 11 January 2012 |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1057/jors.2011.150 | JORS |
Keywords | Field | DocType |
management science,scheduling,investment,operational research,computer science,forecasting,location,production,reliability,information systems,information technology,project management,communications technology,logistics,marketing,inventory,operations research | Mathematical optimization,Tardiness,Scheduling (computing),Computer science,Continuous distributions,Probabilistic logic,Stochastic programming,Operations management,Recursion,Random parameters,Bounding overwatch | Journal |
Volume | Issue | ISSN |
63 | 10 | 0160-5682 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lingrui Liao | 1 | 11 | 1.61 |
| Subhash C. Sarin | 2 | 120 | 16.23 |
| Hanif D. Sherali | 3 | 3403 | 318.40 |