Abstract
The introduction of uncertainty to mathematical programs greatly increases the size of the resulting optimization problems. Specialized methods that exploit program structures and advances in computer technology promise to overcome the computational complexity of certain classes of stochastic programs. In this paper we examine the progressive hedging algorithm for solving multi-scenario generalized networks. We present computational results demonstrating the effect of various internal tactics on the algorithm's performance. Comparisons with alternative solution methods are provided.
Original language | English (US) |
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Pages (from-to) | 399-424 |
Number of pages | 26 |
Journal | Annals of Operations Research |
Volume | 31 |
Issue number | 1 |
DOIs | |
State | Published - Dec 1991 |
All Science Journal Classification (ASJC) codes
- General Decision Sciences
- Management Science and Operations Research
Keywords
- Stochastic networks
- decomposition
- dynamic decision problems
- scenario analysis