Full course description
Stochastic Operations Research:
The objectives of the course are to present fundamentals of probability and stochastic processes from a non-measure theoretic point-of-view to develop (i) basic modeling building and probabilistic reasoning skills, and (ii) an understanding of important qualitative characteristics of some basic stochastic processes used to model dynamical systems with noise. The emphasis is on problem formulation, modeling techniques, realistic applications, and an intuitive grasp of why the techniques work, rather than rigorous mathematical theory. The course is intended to help students develop the ability to “think probabilistically”.
This deficiency exam will cover the following course objectives:
- Introduction to probability theory (sample space and events, conditional probability)
- Random variables (discrete and continuous random variables, distributions, moments, etc.)
- Markov chains (modeling, classification of states, steady state probabilities, etc.)
- Continuous time Markov chains (birth-death process, poisson process, embedded markov chain, etc.)
- Queueing models (Little’s law, markovian queues, networks of queues, etc.)
- Markov decision process (expected total reward, semi-markov process, etc.)
- Develop software artifacts using current software engineering tools
- Conduct software quality assurance
- Document and evaluate software product artifacts and team activities
Who this deficiency exam designed for:
Students who are admitted with deficiencies to graduate programs in Industrial Engineering in the School of Computing, Informatics, and Decision Systems Engineering (CIDSE) at Arizona State University or students who are interested in becoming eligible to apply for this program. Students may also complete this deficiency exam if they have general interest in the topic area or who are looking for a refresher on stochastic operations research.
What you'll receive:
You will receive a certificate of completion with your grade that you can attach in your graduate application for any graduate program within CIDSE. Email your certificate to email@example.com. If you’re a prospective student, you can upload it to your application.
Meet the Deficiency Exam Coordinator
Feng Ju, Assistant Professor, CIDSE
Assistant Professor Feng Ju joined the faculty of the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University in fall 2015. Ju's research interests include stochastic modeling and control in manufacturing and healthcare systems, and battery management systems.
He is a member of the Institute for Operations Research and the Management Sciences (INFORMS), the Institute of Electrical and Electronics Engineers (IEEE), and Insitute of Industrial and Systems Engineers (IISE).