Optimization and Decision Analytics

The course deals with the use of optimization models and other quantitative methods for planning of corporate and governmental activities. Most of the planning problems will consist of an economic objective which we want to maximize/minimize under scarce resources. Relevant planning problems to be studied include production planning and transportation planning. This course deals with both deterministic and stochastic problems, and they will be analyzed based on the following models and methods: Linear and integer programming, network models, decision trees, simple queuing theory and simulation. We will use spreadsheets to find numerical solutions for some of the analyzed problems.

By the end of the course the students should be able to:

• define what is meant by the term "operations research", and account for which phases are normally part of a study applying operations research
• describe the assumptions on which linear programming (LP) is built
• formulate LP models on the basis of verbal problem descriptions
• solve LP problems graphically (for two variables), by using spreadsheets, and by hand using the simplex method
• perform sensitivity analysis and describe the economic information that can be drawn from the analysis
• formulate integer programming models and solve problems formulated using spreadsheets
• formulate and solve a number of network models
• solve certain decision problems under uncertainty with decision trees
• create and derive formulas for some queueing models
• describe discrete event simulation and implement simple simulation models in spreadsheets

Lectures and exercises with and without computers.