The Sample Average Approximation Method for Stochastic Programs with Integer Recourse
The Sample Average Approximation Method for Stochastic Programs with Integer Recourse
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发表时间：
2002
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通讯作者：
Shabbir Ahmed;A. Shapiro
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作者：
Shabbir Ahmed;A. Shapiro
本文给出了一种整数资源两阶段随机规划的求解策略。所提出的方法依赖于通过抽样来逼近潜在的随机规划，并通过专门的优化算法来求解近似问题。我们证明，随着样本容量的增加，所提出的方案将产生真实问题的最优解，并且概率以指数速度逼近1。对于固定的样本量，我们描述了统计和确定性的边界技术来验证候选最优解的质量。文中报告了该方法的初步计算经验。
This paper develops a solution strategy for two-stage stochastic programs with integer recourse. The proposed methodology relies on approximating the underlying stochastic program via sampling, and solving the approximate problem via a specialized optimization algorithm. We show that the proposed scheme will produce an optimal solution to the true problem with probability approaching one exponentially fast as the sample size is increased. For fixed sample size, we describe statistical and deterministic bounding techniques to validate the quality of a candidate optimal solution. Preliminary computational experience with the method is reported.