This lecture provides an introduction and overview of the operations research modeling approach. First, it begins with the origins of the operations research, the nature as well as the impact of the operations research. Later, this lecture also describes all the major steps of a typical operations research study.

This lecture provides the general features of linear programming. First, it begins by developing a miniature prototype example of a linear programming problem. This example is small enough to be solved graphically in a straight-forward way. Next, we present the general linear programming model and its basic assumptions. Lastly, we describe how linear programming models of modest size can be conveniently displayed and solved on a spreadsheet.

This lecture describes and illustrates the main features of the simplex method. It begins by introducing its general nature, including its geometric interpretation. Next, it then develop the procedure for solving any linear programming model that is in "the standard form" (maximization, all functional constraints in <= form, and non-negativity constraints on all variables) and has only non-negative right-hand sides bi in the functional constraints.

This mini lecture discusses some issues in the simplex method, illustrating what to do if the various choice rules of the simplex method do not lead to a clear-cut decision, because of either ties or other similar ambiguities.

So far, we have presented the simplex method under the assumptions that the problem is in the "standard form". In this lecture, we point out how to make the adjustments required for other forms (non-standard), i.e., if the model has negative right-hand sides; variables are allowed to be negative; the model has equality constraints; and the model has functional constraints in ≥ form.