ISyE 3231 Deterministic Operations Research (Summer '99)
Instructor: Spyros Reveliotis
Room #: ISYE 316
Phone #: 894-6608
e-mail: spyros@isye.gatech.edu
Office Hours: 2:00 - 3:00pm TU,TH (or by appointment)
Course Objective
This course is an introduction to Deterministic Operations
Research with emphasis on Linear Programming . During the
class lectures, emphasis will be placed on - the modeling and
analysis of engineering and management problems by means of the above
paradigm, and
- the analytical techniques (algorithms) for the
solution of these problems.
A third objective of the course is
to expose the student to existing computational environments /
packages that implement the theoretical results / algorithms. However,
this objective will be primarily pursued through the homework
assignments.
Course Outline
- Introduction to Operations Research and Mathematical Modeling
- Deterministic OR models:
- Linear Programming (LP) formulations
- Integer Programming (IP) formulations
- Non-linear Programming (NLP) formulations
- Multi-criteria decision making models: Goal Programming (GP)
formulations
- Solving Linear Programming formulations
- Graphical Solution of 2-var LP's
- Generalization to the n-var case, algebraic characterizations
and the fundamental theorem of LP
- The Simplex algorithm
- Solving Goal Programming formulations
- Solving Integer Programming formulations: the Branch \& Bound method
- Introduction to Non-linear optimization
- ``What-if'' and sensitivity analysis for LP problems
- Special LP structures:
- Transportation problems
- Transportation simplex
- Max and Optimal (min-cost) flow problems
- Duality theory (time permitting...)
Course Policies
- Homework Approximately one
per week. It will consist of theoretical problems and/or computing
assignments. Collaboration towards the solution of the homework is
allowed; however, each student must turn in his/her own work
(photocopies will not be accepted). Homework must be turned
in on the specified due date.
- Exams All exams will be closed books, with only 2 pages
of notes allowed. Furthermore, it is expected that your Academic
Honor Code will be respected.
- Grading
- Homework: 25%
- Midterm : 30% (Tentative date: July 8 or 13)
- Final: 45% (Date: TBA)
- Incompletes will be restricted only to very critical
(unavoidable) situations, and will be issued only after substantial
evidence is provided.
- Course GTA's will be available in the undergraduate lab.
Course reading material
- Textbook W. L. Winston, Introduction to
Mathematical Programming: Applications and Algorithms, 2nd ed.,
Duxbury Press
- Reading supplements to be provided in class
- Other useful references (on reserve)
- Rardin, R. L., Optimization in Operations Research ,
Prentice Hall
- Hillier, F.S. & Lieberman, G.J., Introduction to Operations
Research , McGraw Hill (5th Ed.)
- Phillips, D.T., Ravindran, A., & Solberg, J.J., Operations
Research: Principles and Practice, John Wiley & Sons, (2nd Ed.)
- Lawrence, J. A., Jr. & Pasternack, B. A., Applied
Management Science, John Wiley & Sons
- Luenberger, D.G., Linear and Nonlinear Programming,
Addison Wesley (2nd Ed.)
- Bazaraa, M.S., Jarvis, J.J., & Sherali, H.D., Linear
Programming and Network Flows, John Wiley & Sons, (2nd Ed.)
The last two books cited above are for those that might like something
more challenging!
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