Perturbation analysis of general LP models: A unified approach to sensitivity, parametric, tolerance, and more-for-less analysis

Authors:
H. Arsham;M. Oblak
Affiliations:
Department of Information and Quantitative Sciences, University of Baltimore, Baltimore, MD 21201 U.S.A.;Department of Information and Quantitative Sciences, University of Baltimore, Baltimore, MD 21201 U.S.A.
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
1990

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Abstract

This paper develops an alternative approach to postoptimality analysis for general linear programming (LP) problems that provides a simple framework for the analysis of any single or simultaneous change of right-hand side (RHS) or cost coefficient terms for which the current basis remains optimal by solving the nominal LP problem with perturbed RHS terms. Postoptimality analysis of a row or column of the matrix coefficients is also discussed. The goal is a theoretical unification, as well as an advancement in the practical implementation of postoptimality analysis. Some common applications, such as ordinary sensitivity, the 100% rule, and parametric analysis, as well as extensions of recent developments such as tolerance analysis and the more-for-less paradox, are discussed in the context of numerical examples.