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Tatonnement Procedures for Linearly Constrained Convex Optimization

Author

Listed:
  • Markku Kallio

    (IIASA, A-2361 Laxenburg, Austria)

  • Seppo Salo

    (Helsinki School of Economics, Runeberginkatu 14-16, 00100 Helsinki, Finland)

Abstract

The emphasis in this article is to exploit the fact that precision requirements for solutions of most economic models in practice are moderate only. A simple approach is introduced for solving linearly constrained partial equilibrium models based on an iterative scheme similar to the simplex method. It allows large-scale models to be solved, within a practical tolerance, efficiently even in a micro computer environment. Extensions to linearly constrained convex optimization problems are presented. Finally, a set of computational tests on 68 linear programs from the NETLIB library is reported. Comparison of our approach with the simplex method (using MINOS 5.1) and with Karmarkar's algorithm is reported. For moderate precision requirements these preliminary results are highly encouraging.

Suggested Citation

  • Markku Kallio & Seppo Salo, 1994. "Tatonnement Procedures for Linearly Constrained Convex Optimization," Management Science, INFORMS, vol. 40(6), pages 788-797, June.
    • Handle: RePEc:inm:ormnsc:v:40:y:1994:i:6:p:788-797
    DOI: 10.1287/mnsc.40.6.788
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    Cited by:

    1. Markku Kallio & Charles H. Rosa, 1999. "Large-Scale Convex Optimization Via Saddle Point Computation," Operations Research, INFORMS, vol. 47(1), pages 93-101, February.
    2. M.J. Kallio & C.H. Rosa, 1994. "Large-Scale Convex Optimization via Saddle Point Computation," Working Papers wp94107, International Institute for Applied Systems Analysis.

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