However, implementing linear programming can also pose some challenges, such as choosing the right solver, handling non-linearities, dealing with large-scale models, and interpreting the results.

A third way to interpret and communicate linear programming solutions is to use sensitivity analysis, which measures how much the optimal solution changes when you vary the data within certain ranges.

In the classical linear programming problem the behaviour of continuous, nonnegative variables subject to a system of linear inequalities is investigated. One possible generalization of this problem ...