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Generalized linear programming and sensitivity analysis techniques

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  • Emmanuel Macalalag
  • Moshe Sniedovich

Abstract

In this article we report on numerical experiments conducted to assess the performance of c‐programming algorithms for generalized linear programming problems involving the maximization of composite‐convex objective functions. The results indicate that the standard parametric sensitivity analysis techniques of the simplex method can play a central role in such algorithms. We also comment on issues concerning the use of commercial LP packages to solve problems of this type. © 1996 John Wiley & Sons, Inc.

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  • Emmanuel Macalalag & Moshe Sniedovich, 1996. "Generalized linear programming and sensitivity analysis techniques," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(3), pages 397-413, April.
    • Handle: RePEc:wly:navres:v:43:y:1996:i:3:p:397-413
    DOI: 10.1002/(SICI)1520-6750(199604)43:33.0.CO;2-4
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    References listed on IDEAS

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    1. Domingo, Alleli & Sniedovich, Moshe, 1993. "Experiments with dynamic programming algorithms for nonseparable problems," European Journal of Operational Research, Elsevier, vol. 67(2), pages 172-187, June.
    2. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
    3. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    4. Marguerite Frank & Philip Wolfe, 1956. "An algorithm for quadratic programming," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 95-110, March.
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