Managerial Economics Linear Programming

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Managerial Economics Linear Programming Aalto University School of Science Department of Industrial Engineering and Management January 10 – 26, 2017 Dr. Arto Kovanen, Ph.D. Visiting Lecturer

Linear programming– general Many economic problems involve the optimization of a certain objective (e.g., profits) subject to restrictions (e.g., production function) Linear programming is an application of optimization that is frequently applied in many decision-making situations, such production, inventory management, planning, scheduling, and so on In linear programming, both the objective function and the constraints are linear The feasible solution satisfies all the constraints while maximizing (or minimizing) the objective function

Linear programming– general Understand the problem: what is the objective and what is (are) the constraint(s) Write the objective in terms of the decision variables Write the constraints in terms of the decision variable Example 1: maximization problem The company offers two training programs, one of them last two days on team building and the other lasts three days on problem solving. Company management wants to offer at most 6 training programs on teaming during the next 2 months. At most 8 programs are offered during the period. A consultant providing training is paid for 19 days.

Linear programming– general Training program on team building is estimated to bring in $5 (x1,000) and on problem solving $7 (x1,000). Formulate the problem: Let x1 = number of training programs on team building and x2 = number of training programs of problem solving Max the value of V = 5x1 + 7x2 subject to x1 ≤ 6 x1 + x2 ≤ 8 2x1 + 3x2 ≤ 19 X1 ≥ 0, x2 ≥ 0

Linear programming– general What is the feasible region? Draw the constraints and the objective function into the graph (axis are x1 and x2) What is the optimal solution? Please note that not always there is a unique optimal solution

Linear programming– general Sensitivity analysis is a way to evaluate the robustness of the solution This could involve sensitivity of the solution to changes in the coefficients (which may be subject to variation) or the value of the constraints It will allow a manager to have a better understanding of constraints and limits of the problem E.g., the slope of the objective function is different or the budget allows additional days for consultant work

Linear programming– examples Read the following two papers: Example 1: Linear Programming Applications (discussed in class if time permits) Example 2: Introduction to Linear Programming