OR 7230 — Probabilistic Operation Research
4 semester hoursGraduateLectureusually offered: springtypical days: T/FBostonOnlineTraditionalVideo Streaming
Introduces the theory and use of stochastic models to represent industrial operations. Topics include discrete-state Markov chains and applications, state transitions and properties, first passage probabilities, steady-state analysis; absorbing chains and absorption probabilities; introduction to continuous-time Markov chains, transition rates and steady-state analysis; basic elements of queuing systems, birth-and-death process, and special cases; steady-state analysis of simple queuing models including M/M/s, M/M/s/K, M/M/s/N/N and their special cases; and queuing models involving nonexponential distributions.
Prerequisites
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Spring 2024 | 2 | 18 | 50 | 36% | 16.0 |
| Spring 2025 | 1 | 4 | 30 | 13% | 26.0 |
| Spring 2026 | 2 | 7 | 46 | 15% | 19.5 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 0% · T 72% · W 14% · Th 0% · F 86%
Common patterns: TF (72% of sections), async (14% of sections), WF (14% of sections) — in patterns, R means Thursday
Professors
Spring
- Xiaoning Jin (86% of students) · reviews
- Guoyan Li (14% of students)
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (OR course descriptions) · Student reviews on RateMyHusky · All OR courses · Plan it at numap.app