IE 382 - Stochastic Processes

3 lecture hours 0 lab hours 3 credits

Course Description
This course continues the modeling approach to problem solving by presenting techniques used to analyze and design systems affected by random variables. Queuing theory, Markov processes, and decision theory are examined. Case studies and computer algorithms are utilized. (prereq: MA 262, junior standing)

Course Learning Outcomes
Upon successful completion of this course, the student will be able to:

Identify and apply quantitative analysis techniques to engineering problems
Use quantitative management technique results to analyze alternative solutions and assist in decision making
Develop an understanding of how these methods impact business and industry
Improve problem solving skills
Improve communication skills

Prerequisites by Topic

Basic understanding of probability theory and probability distributions

Course Topics

Introduction to Quantitative Management (1 class)
Probability Review (2 classes)
Fundamentals of Decision Theory (3 classes)
Decision Theory and Utility Theory (3 classes)
Project Management (3 classes)
Queuing Theory (5 classes)
Markov Analysis (3 classes)
Simulation (2 classes)
Dynamic Programming (5 classes)
Review (1 class)
Examinations (2 classes)

Coordinator
Aaron Armstrong

Announcement

The Raider Return

Milwaukee School of Engineering

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IE 382 - Stochastic Processes