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On an inverse linear programming problem

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Abstract

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.

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Authors and Affiliations

  1. Institute for Information and Computing Technologies, Almaty, 050010, Kazakhstan

    G. A. Amirkhanova

  2. Dorodnitsyn Computing Center, Russian Academy of Sciences, Moscow, 119333, Russia

    A. I. Golikov & Yu. G. Evtushenko

Authors
  1. G. A. Amirkhanova
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  2. A. I. Golikov
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  3. Yu. G. Evtushenko
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Corresponding author

Correspondence to A. I. Golikov.

Additional information

Original Russian Text © G.A. Amirkhanova, A.I.Golikov, Yu.G. Evtushenko, 2015, published in Trudy Instituta Matematiki i Mekhaniki UrO RAN, 2015, Vol. 21, No. 3.

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Amirkhanova, G.A., Golikov, A.I. & Evtushenko, Y.G. On an inverse linear programming problem. Proc. Steklov Inst. Math. 295 (Suppl 1), 21–27 (2016). https://doi.org/10.1134/S0081543816090030

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  • DOI: https://doi.org/10.1134/S0081543816090030

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