THEORETICAL FRAMEWORK FOR STOCHASTIC PROGRAMMING

被引：0
|
作者：
Novotny, Jan [1 ]
机构：
[1] Brno Univ Technol, Inst Math, Brno 61669, Czech Republic
来源：
MENDELL 2009 | 2009年
关键词：
Stochastic programming; Two-stage stochastic programming; Separable function; Here-and-now; Wait-and-see; Probability;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper aims to present a theoretical framework for stochastic programming models, i.e. for optimization models that involve uncertainty. The framework is characterized by two distinctive features: it is based on the notions of a mathematical program and a probability space. Based on these, it allows the common stochastic programming models to be rigorously derived, and hopefully well understood. Such approach is not common in the literature (See Reference), the stochasticity is generally introduced to a deterministic program after it has been built.
引用
收藏
页码：239 / 246
页数：8
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