OR / STAT 645

Stochastic Processes

Fall 2012

Important Announcements & Deadlines

HW#4 due at 7:20 PM, Thursday, November 29.
Reading materials for the class (in any electronic format) is due at 12:01PM, Monday of the week of your presentation.
Three quiz questions with solution (in word doc format) is due at 12:01PM, Monday of the week of your presentation.
Power Point Presentation is due 24 hours before your presentation.
Midterm Exam will be held on Thursday, November 1. 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.
A good follow-up class: OR 735 Advanced Stochastic Simulation.

Instructor: Chun-Hung Chen
Email: cchen9@gmu.edu
Office: Engineering Building, Room 2213
Phone: 703-993-3572
Fax: 703-993-1521
Office Hours: Thursday 4:00 - 6:00 PM

Teaching Assistant: TBA

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% (the lowest one will be dropped).

Required Text: S. Ross, Introduction to Probability Models (any edition beyond 8^th is fine).

Exams:
Midterm Exam will be held in class on Thursday, November 1. 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	3	Chapter 5
3	Markov chains	3	Chapters 4 & 6
4	Renewal theory	1	Chapter 7
5	Brownian motion	1.5	Chapter 10
6	Study and presentation of applications and advanced topics	3	Chapters 7 & 10, and handouts

Project Presentation Schedule:

Date	Topics	Member 1	Member 2
11/15	A. Poisson Process Applications	Schorer
11/15	C. Hidden Markov Chains	Strazzeri	Wilson
11/29	D. Markov Decision Processes	Nguyen	Harper
11/29	F. Applications of Brownian Motion	Gryphon	Mahoney
12/6	B. Markov Chain General Applications	El Beleidy	Vukolic
12/6	E. Markov Chain Monte Carlo	Kuchel

Homework Assignments & Others

Go to Professor Chun-Hung Chen's Page