Abstract
A continuing priority in sensitivity and parametric analysis is to develop approaches that provide useful information, that are easy for a decision-maker to use, and that are computationally practical. Herein we review approaches to sensitivity analysis in linear programming and discuss how they meet the above needs. Special emphasis is given to sensitivity analysis of the objective function coefficients.
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