WHEN RESTRICTIVE CONSTRAINTS ARE NONBINDING - ILLUSTRATIONS AND IMPLICATIONS

被引:1
|
作者
MARTINICH, JS
机构
[1] School of Business Administration, University of Missouri-St. Louis, St Louis, Missouri, 63121
关键词
DECISION PROCESSES; MATHEMATICAL PROGRAMMING; SENSITIVITY ANALYSIS; STRATEGY AND POLICY;
D O I
10.1111/j.1540-5915.1991.tb01261.x
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
For convex and concave mathematical programs restrictive constraints (i.e., their deletion would change the optimum) will always be binding at the optimum, and vice versa. Less well‐known is the fact that this property does not hold more generally, even for problems with convex feasible sets. This paper demonstrates the latter fact using numerical illustrations of common classes of problems. It then discusses the implications for public policy analysis, econometric estimation, and solution algorithms. Copyright © 1991, Wiley Blackwell. All rights reserved
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页码:53 / 59
页数:7
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