OR / STAT 645

Stochastic Processes

Fall 2009

Important Announcements & Deadlines

Reading materials for the class (in any electronic format) is due 6 days before your presentation.
Three quiz questions with solution (in word doc format) is due 6 days before your presentation.
Power Point Presentation is due 24 hours before your presentation.
HW#4 due at 7:20 PM, Tuesday, December 1. (Skip problem 3)
Midterm Exam will be held on Tuesday, October 27. Make up exam questions will be MUCH MORE DIFFICULT than regular exam questions.
Reminder: some announcements will be sent to your GMU email address. Please check your GMU emails routinely or ensure that they are forwarded correctly.

Instructor: Chun-Hung Chen
Email: cchen9@gmu.edu
Office: Engineering Building (Academic VI), Room 2213
Phone: 703-993-3572
Fax: 703-993-1521
Office Hours: Tuesday 5:00 - 6:00 PM and Wednesday 3:30 - 4:30 PM

Teaching Assistant: Mr. Ben Crain
Email: bcrain@gmu.edu
Office: Engineering Building (Academic VI), Room 2216
Office Hours: Monday 5:30 - 6:30 PM, or by appointment.

Course Description:

Selected applied probability models including Poisson processes, discrete- and continuous-time Markov chains, renewal and regenerative processes, semi-Markov processes, queuing and inventory systems, reliability theory, and stochastic networks. Emphasis is on applications in practice as well as analytical models.

Prerequisites: OR 542, STAT 544, or permission of instructor.

Grading: Homework 15%; Midterm 30%; Term Project 40%, Quiz in class 15% (lowest ones will be dropped).

Required Text: S. Ross, Introduction to Probability Models, 9th Ed.

Exams:
Midterm Exam will be held in class on Tuesday, October 27. There is no final exam. Make up exam questions will be MUCH MORE DIFFICULT than regular exam questions.

General Rules:

Late homework and term project report is always allowed. No need to get advanced permission. However, the penalty for late homework is 25% for the first day and then 5% per day. No exemption.
Turning in HW through email is subject to a 20% penalty; but fax is OK.
No collaborations are allowed for homework, although discussions are encouraged.
Comments are strongly encouraged.
No cheating.

Course Schedule & Reading Assignment:

	Topics	Time (week)	Reading Assignment
0	Introduction	0.5
1	Probability review	1	Chapters 1~3
2	Exponential distribution and Poisson process	2.5	Chapter 5
3	Markov chains	3	Chapters 4 & 6
4	Renewal theory	1	Chapter 7
5	Brownian motion	1	Chapter 10
6	Study and presentation of applications and advanced topics	4	Chapters 7 & 10, and handouts

Project Presentation Schedule:

Date	Topics	Member 1	Member 2
11/17	B. Markov Chain Application 1	Escalera	Comer
11/17	F. Sections 7.3 & 7.4	Davis	Fell
11/24	A. Poisson Process Applications	Jarvandi	Kullarni
11/24	G. Section 7.5 & 7.8	Neely	Huggins
11/24	J. Application of Brownian Motion	Menton	Franklin
12/1	C. Markov Chain Application 2	Mitra	Goldstein
12/1	H. Section 7.10	Laubis	O'Neil
12/1	I. Sections 10.3 and 10.4	Lewis	Lin
12/8	D. MC Model of Section 8 Rent Burden	Mast	X
12/8	E. Markov Chain Monte Carlo	Anderson	Baumgartner
12/8	K. Simulation of Brownian motion	Blaho	Graziano

Homework Assignments & Others

Go to Professor Chun-Hung Chen's Page