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Algorithmic insights and a convergence analysis for a Karmarkar‐type of algorithm for linear programming problems

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  • Hanif D. Sherali

Abstract

This paper is concerned with a modification of a recently proposed variant of Karmarkar's algorithm for solving linear programming problems. In analyzing this variant, we exhibit interesting and useful relationships of these types of algorithms with barrier function methods, and subgradient optimization procedures involving space dilation techniques, which subsume the well‐known ellipsoidal type of algorithms. Convergence of this variant is established under certain regularity conditions. We also provide remarks on how to obtain dual variables or Lagrange multipliers at optimality.

Suggested Citation

  • Hanif D. Sherali, 1987. "Algorithmic insights and a convergence analysis for a Karmarkar‐type of algorithm for linear programming problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(3), pages 399-416, June.
    • Handle: RePEc:wly:navres:v:34:y:1987:i:3:p:399-416
    DOI: 10.1002/1520-6750(198706)34:33.0.CO;2-6
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    References listed on IDEAS

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    1. Bazaraa, Mokhtar S. & Sherali, Hanif D., 1981. "On the choice of step size in subgradient optimization," European Journal of Operational Research, Elsevier, vol. 7(4), pages 380-388, August.
    2. Nickels, W. & Rodder, W. & Xu, L. & Zimmermann, H. -J., 1985. "Intelligent gradient search in linear programming," European Journal of Operational Research, Elsevier, vol. 22(3), pages 293-303, December.
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    Cited by:

    1. Hanif D. Sherali & Bradley O. Skarpness & Buyong Kim, 1988. "An assumption‐free convergence analysis for a perturbation of the scaling algorithm for linear programs, with application to the L1 estimation problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(5), pages 473-492, October.
    2. K. O. Kortanek & Zhu Jishan, 1988. "New purification algorithms for linear programming," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(4), pages 571-583, August.

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