NONPARAMETRIC APPROACH TO STOCHASTIC LINEAR-PROGRAMMING

被引：1

作者：

SENGUPTA, JK

机构：

[1] University of California, Santa Barbara, CA

来源：

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE | 1993年 / 24卷 / 05期

关键词：

D O I：

10.1080/00207729308949529

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A class of non-parametric methods based on the minimax solution is developed here for models of stochastic linear programming. These methods provide a measure of robustness through the adoption of a cautious policy. The usefulness of these methods is illustrated through data envelopment analysis which utilizes an optimizing method of efficiency measurement.

引用

页码：857 / 871

页数：15

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