This is a preview. Log in through your library . Abstract Traditional sensitivity analysis of linear programming objective function coefficients concerns itself with variations in single parameters.

The objective coefficient ranging analysis, discussed in the last example, is useful for accessing the effects of changing costs and returns on the optimal solution if each objective function ...

We propose a parameter estimation method based on what we call the minimum decisional regret principle. We focus on mathematical programming models with objective functions that depend linearly on ...

Now, linear programming, or LP as we like to call it, is quite a handy mathematical tool. It helps optimize a goal, which we call an objective function, while keeping in mind some linear constraints ...

If the constrained problem to be solved has no nonarc variables, then Q, d, and z do not exist. However, nonarc variables can be used to simplify side constraints. For example, if a sum of flows ...