
8
Linear Optimization under Uncertainty
8.1 Introduction
A fundamental assumption in linear programming is that the coefficients are
assumed to be known. In other words, all of the linear programs up to now
have been deterministic problems. However, in reality, these quantities are at
best estimations, and in many instances parameters are essentially random
values and thus it is often a challenge to select parameter values for a model.
Sensitivity analysis, developed in Chapter 4, may shed light on the range
of data perturbations for a linear program that is allowed while keeping the
original optimal solution optimal. However, there are several limitations. ...