A global tolerance approach to sensitivity analysis in linear programming

This paper takes a fresh look at sensitivity analysis in linear programming. We propose a merged approach that brings together the insights of Wendell's tolerance and Wagner's global sensitivity approaches. The modeler/analyst is then capable of answering questions concerning stability, trend, model structure, and data prioritization simultaneously. Analytical as well as numerical aspects of the approach are discussed for separate as well as simultaneous variations in the objective function coefficients and right-hand side terms. A corresponding efficient numerical implementation procedure is proposed. A classical production problem illustrates the findings.