Logistics

Time & Days TuTh 9:00AM - 10:30AM
Location 1층 공동강의실
Instructor Kihyuk Hong (E2-2 #3104)
Office Hours W 2:00 - 3:00 pm (E2-2 #3104)
Email [email protected]
TAs • Mingyu Yang (양민규, [email protected])
• Daho Chun (천다호, [email protected])
Textbook Introduction to Probability Models, 12th Edition”, by Sheldon M. Ross.
Github ‣

Course Description

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.

Grading

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%

Course Schedule

No. Date Topics Readings Resources
01 Sep 02 Introduction. - Introduction
02 Sep 04 Random variables Ch 1.2-6, 2.1-3 PT1
03 Sep 09 Random variables Ch 2.4,2.5 PT2
04 Sep 11 Discrete random variables Ch 2.2 PT3
05 Sep 16 Continuous random variables Ch 2.3,2.6 PT4
06 Sep 18 Limit theorems Ch 2.7,2.9 PT5
07 Sep 23 Conditional probability & expectations Ch 3.1-3.7 PT6
08 Sep 25 Applications - PT7
09 Sep 30 Bandit Problem BP1
10 Oct 02 Markov Chains Ch 4.1,4.2 MC1
Chuseok
11 Oct 14 Classification of states Ch 4.3,4.4 MC2
12 Oct 16 Limiting distribution Ch 4.4 MC3
13 Oct 21 Midterm
14 Oct 23 Some applications Ch 4.4-6 MC4
15 Oct 28 MDP Ch 4.10 MC5
16 Oct 30 Exponential distribution Ch 5.2 PP1
17 Nov 04 Poisson process Ch 5.3 PP2
18 Nov 06 Exercises Ch 5.3 PP3
19 Nov 11 CTMC Ch 5.4-5, 6.1-2 PP4
20 Nov 13 Renewal process Ch 7.1-4 RN1
21 Nov 18 Applications Ch 7.5,7.7,7.9 RN2
22 Nov 20 Exponential models Ch 8.1-3 QT1
23 Nov 25 Network of Queues Ch 8.3-4 QT2
24 Nov 27
25 Dec 02
26 Dec 04
27 Dec 09
28 Dec 11
29 Dec 16 Final - -