| Semester | Fall 2025 |
|---|---|
| Time & Days | TuTh 9:00AM - 10:30AM |
| Location | E2-2 #1501 |
| Instructor | Kihyuk Hong (E2-2 #3104) |
| Office Hours | M 3:00 - 4:00 pm (E2-2 #3104) |
| [email protected] | |
| TAs | • Mingyu Yang (양민규, [email protected]) |
| • Daho Chun (천다호, [email protected]) | |
| Textbook | Introduction to Probability Models, 12th Edition, by Sheldon M. Ross. |
| Code | ‣ |
| Website | https://www.kihyukhong.com/ie232 |
| Midterm | Oct 21 (T) 9:00 - 11:45 am. E2 #1501 |
| Final | Dec 16 (T) 9:00 - 11:45 am. E2 #1501 |
This course covers mathematical models and analytical techniques essential for performance evaluation and decision-making in the rational design and operation of engineering systems subject to stochastic variability—such as production and manufacturing systems, computer and communication systems, and service systems. Key topics include the fundamentals of stochastic processes, Poisson processes and arrival process models, Markov chain models, queueing models, reliability models, decision analysis models, Markov decision processes, and stochastic simulation. Students will learn core concepts, modeling methodologies, and analytical tools for these areas. Prerequisite: IE241 or permission of the instructor.
| Components | Note | % |
|---|---|---|
| Participation | In-class participation (attendance, polls) | 10% |
| Homework | 4 homework sets | 20% |
| Mini Project | Modeling/simulation/analysis of a real-world stochastic system | 10% |
| Midterm Exam | In-class | 30% |
| Final Exam | In-class | 30% |
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Subject to change.
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| No. | Date | Lecture Notes | Readings | 📹 | Homework |
|---|---|---|---|---|---|
| 01 | Sep 02 | Lecture 01: Introduction. | notebook | ||
| 02 | Sep 04 | Lecture 02: Probability Theory 1 — Introduction to probability theory | Ch 1.2-6, notebook | HW1-1 | |
| 03 | Sep 09 | Lecture 03: Probability Theory 2 — Discrete random variable | Ch 2.1-2,2.4-5 | ||
| 04 | Sep 11 | Lecture 04: Probability Theory 3 — Poisson distribution, Continuous random variables | Ch 2.2,2.3 | ▶️ | HW1-2 |
| 05 | Sep 16 | Lecture 05: Probability Theory 4 — Exponential distribution | Ch 2.3, Ch 3, Ch 5.2 | ||
| 06 | Sep 18 | Lecture 06: Poisson Process 1 — Poisson process definition and properties | Ch 5.3, notes | ▶️ | HW1-3 |
| 07 | Sep 23 | Lecture 07: Poisson Process 2 — Properties of Poisson processes and their applications | Ch 5.3, notebook | ▶️ | |
| 08 | Sep 25 | Lecture 08: Poisson Process 3 — Compound Poisson process, nonhomogeneous Poisson process | Ch 5.4.1, 5.4.2 | ▶️ | **HW2-1, P3.ipynb** |
| 09 | Sep 30 | Lecture 09: Queueing Theory 1 — Little’s Law, M/M/1 Queueing System, M/M/1 Queueing System with finite capacity | Ch 8.1-3 | ▶️ | |
| 10 | Oct 02 | Lecture 10: Queueing Theory 2 — Shoe shine shop, Bulk service, Network of queues | Ch 8.3-4 | ▶️ | HW2-2 |
| Chuseok | |||||
| 11 | Oct 14 | Lecture 11: Practice problems | practice problems | ▶️ | |
| 12 | Oct 16 | Lecture 12: Midterm review. practice problems sample solution, sample midterm solution | sample midterm | ▶️ | |
| Oct 17 | HW2 due | ||||
| Oct 21 | Midterm: 9:05 ~ 11:35 am E2 #1501 | ||||
| 13 | Oct 28 | Lecture 13: Markov Chains | Ch 4.3,4.4 | ||
| 14 | Oct 30 | Classification of states | Ch 4.4 | ||
| Oct 31 | Proposal due | ||||
| 15 | Nov 04 | Limiting distribution | Ch 4.4-6 | ||
| 16 | Nov 06 | Some applications | Ch 4.10 | ||
| 17 | Nov 11 | MDP | Ch 7.1-4 | ||
| 18 | Nov 13 | Renewal process | Ch 7.5,7.7,7.9 | ||
| 19 | Nov 18 | Applications | |||
| 20 | Nov 20 | ||||
| 21 | Nov 25 | ||||
| Nov 27 | No lecture | ||||
| 22 | Dec 02 | ||||
| 23 | Dec 04 | Limit theorems | Ch 2.7,2.9 | ||
| 24 | Dec 09 | Bandit Problem | |||
| 25 | Dec 11 | ||||
| Dec 16 | Final | - | - | ||
| Dec 19 | Project due |
The slides have evolved over the years, with contributions from J. R. Morrison, K. Kim, H.-J. Kim, and S. Min.