ABSTRACT
This chapter discusses several programming models – linear, integer, dynamic, heuristic, and goal programming. It provides more attention to linear programming than the rest. The simplest way to solve a linear programming problem is to use a graphical approach – since it makes it easier to visualize the problem, especially when one is dealing with two decision variables and a limited number of constraints – and follow the solution process. The simplex method provides an iterative (step-by-step) solution for the linear programming problem. It does so, first, by converting the constraints to equations; second, by defining a set of new variables called the basic variables; third, by finding an initial feasible solution for the problem; and, finally, by continuing the search for an improved solution. An important contribution of the simplex method, other than finding the optimal solution, is that it produces a variety of information that policy makers will find useful for making allocation and other decisions.
