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Calculating some inverse linear programming problems. (English) Zbl 0856.65069
For the general linear programming problem \[ \min \{cx/Ax = b,\;x \geq 0\} \] the inverse problem is expressed as \[ \min \bigl\{ |c-\widetilde c|/ \widetilde c\in F(x^0) \bigr\} \] where \(c,x \in \mathbb{R}^n\), \(b \in \mathbb{R}^m\), \(A\) is an \(m \times n\) matrix, \(x^0\) is a feasible solution, \[ F(x^0) = \bigl\{\widetilde c \in \mathbb{R}^n/ \min \{\widetilde cx/Ax=b,\;x\geq 0\} = \widetilde cx^0 \bigr\} \] and \(|\dots|\) is the \(l_1\) norm. A method for solving this inverse problem is suggested which is based on the optimality conditions for linear programming problems. For the application of the given method to inverse minimum cost flow or assignment problems is found that this method yields strongly polynomial algorithms.

MSC:
65K05 Numerical mathematical programming methods
90C05 Linear programming
90B80 Discrete location and assignment
90B10 Deterministic network models in operations research
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