A general algorithm for solving two-stage stochastic mixed 0–1 first-stage problems
We present an algorithmic approach for solving large-scale two-stage stochastic problems having mixed 0–1 first stage variables. The constraints in the first stage of the deterministic equivalent model have 0–1 variables and continuous variables, while the constraints in the second stage have only c...
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| Vydáno v: | Computers & operations research Ročník 36; číslo 9; s. 2590 - 2600 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Kidlington
Elsevier Ltd
01.09.2009
Elsevier Pergamon Press Inc |
| Témata: | |
| ISSN: | 0305-0548, 1873-765X, 0305-0548 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | We present an algorithmic approach for solving large-scale two-stage stochastic problems having mixed 0–1 first stage variables. The constraints in the first stage of the deterministic equivalent model have 0–1 variables and continuous variables, while the constraints in the second stage have only continuous. The approach uses the
twin node family concept within the algorithmic framework, the so-called
branch-and-fix coordination, in order to satisfy the
nonanticipativity constraints. At the same time we consider a scenario cluster Benders decomposition scheme for solving large-scale
LP submodels given at each
TNF integer set. Some computational results are presented to demonstrate the efficiency of the proposed approach. |
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| Bibliografie: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 |
| ISSN: | 0305-0548 1873-765X 0305-0548 |
| DOI: | 10.1016/j.cor.2008.11.011 |