1. INFM 718A / LBSC 705 Information For Decision Making Lecture 4

2. Overview Linear Programming Recap –Modeling –Graphical Solution Approach –In-Class Exercises 2.2 and 2.3 Excel Solution Approach (Solver) –Maximization Example –In-Class Exercises 2.1, 2.2 and 2.3 in Solver –Minimization Example

3. Linear Programming Decision models that involve decision variables whose feasible values are bounded by a set of constraints, aiming to maximize utility/profit, or minimize loss/cost.

4. Modeling LP Problems What are the decision variables? What is the goal (max./min.)? Maximize/Minimize what? What are the constraints?

5. Modeling

6. Graphical Solution

7. Solve for inequalities that intersect at the Optimal Solution Point.

8. In-Class Exercises 2.2 2.3

9. Excel Approach (Solver) Build a spreadsheet representation of the model. Define the target cell, max./min and constraints in Solver Let Solver solve.

10. Spreadsheet Representation Decision variables Values of decision variables at optimal solution point. (Leave blank.) Constraints Contributions to objective function Value of objective function at OSP. Cells in red type are formulas; other cell values are entered manually.

11. Solver Definition

15. Let Solver Solve

16. Solver Solution

17. Exercises Solve the following using Solver: –Maximization Example –In-Class Exercises 2.1, 2.2, and 2.3 –Minimization Example