PERTURBATION ANALYSIS OF GENERAL LP MODELS - A UNIFIED APPROACH TO SENSITIVITY, PARAMETRIC, TOLERANCE, AND MORE-FOR-LESS ANALYSIS

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. © 1990.