| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1007/BF02187640 |
| Parallel decomposition of large-scale stochastic nonlinear programs. | |
| Birge J; Rosa C | |
| 发表日期 | 1996 |
| 出处 | Annals of Operations Research 64 (1): 39-65 |
| 出版年 | 1996 |
| 语种 | 英语 |
| 摘要 | Many practical decision problems involve both nonlinear relationships and uncertainties. The resulting stochastic nonlinear programs become quite difficult to solve as the number of possible scenarios increases. In this paper, we provide a decomposition method for problems in which nonlinear constraints appear within periods. We also show how the method extends to lower bounding refinements of the set of scenarios when the random data are independent from period to period. We then apply the method to a stochastic model of the U.S. economy based on the Global 2100 method developed by Manne and Richels. |
| 关键词 | Decomposition Economics Environment Parallel computation Stochastic programming |
| URL | http://pure.iiasa.ac.at/id/eprint/13586/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/127450 |
| 推荐引用方式 GB/T 7714 | Birge J,Rosa C. Parallel decomposition of large-scale stochastic nonlinear programs.. 1996. |
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