Perhaps more aptly titled "Optimization for the Management Student," this course is designed to teach students the basic optimization tools and analytic problem solving skills required for decision making in business. We will learn how to:
- Structure a decision problem: identifying the objective, decision alternatives (i.e., outputs), input parameters, and sources of uncertainty.
- Build a mathematical model to formalize the decision problem: We will learn about
- Optimization models (linear, nonlinear) - for resource allocation (how to utilize available resources optimally)
- Decision tree models - for multiperiod sequential decision making
- Simulation models - for risk analysis and incorporating uncertainty in problem parameters.
- Analyze model solution: Is the decision fairly robust, or very sensitive to the input parameters of the model ? What is the managerial interpretation of the model solution?
- use Microsoft Excel as a platform for model building, solution, and analysis: In addition to standard Excel tools such as Goal Seek and Data Table, we will learn to use important Excel add ons such as Sensitivity Toolkit, Solver, SolverTable, Precision Tree, @RISK, and RiskOptimizer. These tools can also be used in other Booth classes.
The lectures will be structured as a brief introduction to an optimization model (its strengths, weaknesses) followed by an interactive discussion of a few (3-5) chosen toy problems from business areas including operations, marketing, finance, and strategy. We will develop the optimization models for these problems and implement them in Excel.