In Chapters 2 and 3, two basic linear programming models, one for a maximization problem and one for a minimization problem, were used to demonstrate model formulation, graphical solution, computer solution, and sensitivity analysis. Most of these models were very straightforward, consisting of only two decision variables and two constraints. They were necessarily simple models so that the linear programming topics being introduced could be easily understood .
In this chapter, more complex examples of model formulation are presented. These examples have been selected to illustrate some of the more popular application areas of linear programming. They also provide guidelines for model formulation for a variety of problems and computer solutions with Excel and QM for Windows.
You will notice as you go through each example that the model formulation is presented in a systematic format. First, decision variables are identified, then the objective function is formulated, and finally the model constraints are developed. Model formulation can be difficult and complicated, and it is usually beneficial to follow this set of steps in which you identify a specific model component at each step instead of trying to "see" the whole formulation after the first reading.