San Jose State University

Department of Computer, Information and Systems Engineering Department

Industrial & Systems Engineering Program

ISE 230 – Advanced Operations Research

Spring 2000

Course Objectives

To study advanced operations research techniques and topics related to industrial and systems engineering; to learn the use of software in solving problems. When the course is completed, the student should be able to apply OR techniques to real-world problems. The techniques will be fully motivated with concrete and real work examples. Mathematical facts will be presented with geometric and economic motivation. Their rigorous mathematical proofs will not be the focus, but the facts will be substantiated with “guided intuition.” Among many examples to be discussed are those that relate to assembly/production line design.

Course Conduct

This class will meet once a week. The software that comes with the textbook is learning/demonstration oriented; you will be expected to use the software readily for homework problems, presentations and exams. There will be homework assignments, one midterm exam and one final exam. Participation in class discussion is encouraged.

Course Content

Approximately one third of the class time will be devoted to deterministic models and optimization techniques: linear programming, network models (shortest path problems, CPM, PERT, etc.), etc. The rest will be spent on stochastic models and optimization techniques: Markov Chain, queueing theory, decision analysis.

Course Prerequisite ISE 170 – Introduction to Operations Research

Textbook “Operations Research: Applications and Algorithms” by

Wayne L. Winston, (3rd Edition), Duxbury,1994 (including

software).

Grading

Homework 40%

Midterm 30%

Final 30%

Instructor H.-S. Jacob Tsao and We-Min Chow

Telephone: (408) 924-4088 (408) 986-7179

FAX: (408) 924-4153

E-mail:

Office Hours: Mon. 1:00 – 3:00;

Mon. 3:30 – 5:00;

Wed. 10:30 – 12:00
ISE 230 Syllabus (Continued)

Week Date Chapter Topics

1 1/26 1,2,3 Course Overview

Introduction to Linear Programming

2 2/2 4, handouts The Simplex Method

3 2/9 5,6,10 Advanced Topics on Linear Programming

4  2/16 8 More IE Applications: CPM, PERT, etc

5  2/23 19 Fundamentals of Stochastic Processes

Basic Discrete Stochastic Processes

Markov Chains

6 3/1 8, handouts Markov Chains (Cont’d)

Basic Continuous-Time Stochastic Processes

Poisson Processes

Non-homogeneous Poisson Processes

7 3/8 22 Overview of Queueing Theory

8 3/15 22 Stochastic Processes in Queuing Theory

9  3/22 22, handouts Mid-term

Stochastic Processes in Queuing Theory (cont’d)

10  3/29 Spring Break

11  4/5 22 Simple Queues with Random Arrival and Exponential

Service Time

12  4/12 22 Simple Queues with Random Arrival and Exponential

Service Time (continued)

Queues with General Service Time Distribution

13 4/19 22, handouts Queues with General Service Time Distribution (Cont’d)

14 4/26 handouts Network of Queues and Its Applications

15 5/3 handouts Special Topics in Queues

16 5/10 13,14 Decision-Making Under Uncertainty