Course Details

Course Number: 95-760

Decision Making Under Uncertainty

Units: 6

Managers in general, including information systems managers, constantly make decisions. Rarely are they lucky enough to have "full information ". Decision making under uncertainty is the norm. This class teaches a range of quantitative methods for making practical decisions under uncertainty, and in doing so gives an intense introduction into the art of mathematical modeling of business and social systems. The methods covered include forecasting, queuing theory and Monte Carlo simulation. Some deterministic optimization methods will also be covered. The emphasis will be on "end user modeling " that equips the students to use these methods to inform his or her own future decision making, but where appropriate will be extended to consider construction of decision support systems generally.

Learning Objectives:

1. Develop a conscience of linear optimization, network modeling, forecasting and queuing theory.
2. Develop techniques for solving LP problems in a spreadsheet and Network problems in spatial analysis and for doing LP sensitivity analysis.
3. Have confidence in the ability to perform simulation using ‘Cristal Ball’ and integer optimization.
4. Discuss heuristics and biases in decision making.

Syllabus

Faculty:
Jonathan P. Caulkins
Haijing Hao
Stephen F. Roehrig
David Choi