1 (1.1). Describe 7 main steps in scientific decision making. Illustrate the steps using a specific management problem (for an example, choice of inputs for a PC with minimal costs ).

2 (2.1). Define a linear programming model and its components. Discuss which 3 properties a planning problem needs to meet to be modeled as a LP.

3 (2.2). Define feasible set and its corner points. Explain how one can find the combinations of the decision variables corresponding to the corner points. How one can use the corner points to find the optimal solution?

4 (2.3). Define special situations: unbounded feasible set, infeasibility, alternate solutions, redundant constraints. Discuss what do these situations imply for the manager's planning problem. When do you need to and how do you avoid this situations?

5 (3.1) Provide an example of a manufacturing or employee staffing application discussed in the class (based on chapter 3). State the business problem; name the decision variables; define the objective function; explain sources of the linear constraints in this application.

6 (3.2) Provide an example of a marketing or transportation application discussed in the class (based on chapter 3). State the business problem; name the decision variables; define the objective function; explain sources of the linear constraints in this application.

7 (3.3) Provide an example of a finance or blending application discussed in the class (based on chapter 3). State the business problem; name the decision variables; define the objective function; explain sources of the linear constraints in this application.

8 (3.4) Provide an example of a multi-period application discussed in the class (based on chapter 3). State the business problem; name the decision variables; define the objective function; explain sources of the linear constraints in this application.