The Sample Average Approximation Method Applied to Stochastic Routing Problems: A Computational Study

被引：0
|
作者：
Bram Verweij
Shabbir Ahmed
Anton J. Kleywegt
George Nemhauser
Alexander Shapiro
机构：
[1] Georgia Institute of Technology,School of Industrial and Systems Engineering
来源：
Computational Optimization and Applications | 2003年 / 24卷
关键词：
stochastic optimization; stochastic programming; stochastic routing; shortest path; traveling salesman;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The sample average approximation (SAA) method is an approach for solving stochastic optimization problems by using Monte Carlo simulation. In this technique the expected objective function of the stochastic problem is approximated by a sample average estimate derived from a random sample. The resulting sample average approximating problem is then solved by deterministic optimization techniques. The process is repeated with different samples to obtain candidate solutions along with statistical estimates of their optimality gaps.
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页码：289 / 333
页数：44
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