On an Inverse Linear Programming Problem

被引：3

作者：

Amirkhanova, G. A. ^{[1
]}

Golikov, A. I. ^{[2
]}

Evtushenko, Yu. G. ^{[2
]}

机构：

[1] Inst Informat & Comp Technol, Alma Ata 050010, Kazakhstan

[2] Russian Acad Sci, Dorodnitsyn Comp Ctr, Moscow 119333, Russia

来源：

PROCEEDINGS OF THE STEKLOV INSTITUTE OF MATHEMATICS | 2016年 / 295卷 / 01期

基金：

俄罗斯基础研究基金会;

关键词：

linear programming; inverse linear programming problem; duality; unconstrained optimization; generalized Newton method; NEWTON METHOD;

D O I：

10.1134/S0081543816090030

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A method for solving the following inverse linear programming (LP) problem is proposed. For a given LP problem and one of its feasible vectors, it is required to adjust the objective function vector as little as possible so that the given vector becomes optimal. The closeness of vectors is estimated by means of the Euclidean vector norm. The inverse LP problem is reduced to a problem of unconstrained minimization for a convex piecewise quadratic function. This minimization problem is solved by means of the generalized Newton method.

引用

页码：S21 / S27

页数：7

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