Stochastic Processes (4 Credits)
Learning Outcomes:
On successful completion of this course students will be able to: Design a system when randomness is significant; Describe the effect of variability into a system’s behavior and performance; Apply Markov Chains to various kinds of problems; Apply basic inventory models; Define key concepts in production flow (i.e. bottlenecks, line balancing, and Little’s Law); Use open and closed Jackson networks and maintain throughput in a closed Jackson network and compute corresponding WIP levels.
Topics:
- Probability and Random Variables
- Discrete-Time Markov Chains
- Poisson Process
- Continuous-Time Markov Chains
- Renewal Process
- Queuing Theory
- Reliability Theory
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