BUAN 5260 - Mathematical Models for Decision-Making

3 credit hours
This course introduces several important modeling approaches for decison-making problems. The first part of the course focuses on deterministic optimization problems including linear, integer, and possibly dynamic programming. Applications that may be used during the course include: allocation of advertising and sales effort, artificial intelligence models, revenue management, production and distribution system planning. The second part of the course addresses decision-making under uncertainty. Topics include: a brief review of probability theory, an introduction to stochastic processes, and Monte Carlo simulation. Illustrations used during this part of the course may be drawn from areas such as consumer behavior ( learning, purchase timing, purchase incidence, or brand choice), scheduling of operations, performance of computing systems, and sales forecasting. The emphasis throughout is on understanding the problem, formulating a suitable model, finding a solution, interpreting it, and performing sensitivity analysis. The course seeks to provide an intuition for how different techniques work, along with experience in applying them to real problems, and in presenting results and recommendations in a clear and persuasive manner to specialists and non-specialists alike. Students will complete a short, collaborative term project that requires them to recognize, model, and solve a real-world problem using the methods learned in the course.

Registration Restriction(s): MSBA students only
Prerequisite Course(s): ECON 5100, BUAN 5310
Prerequisite or Co-requisite Course(s):
ECON 5100, BUAN 5310