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来源类型Article
规范类型其他
DOI10.1007/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
URLhttp://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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