COURSE SYLLABUS

IE 417        SPECIAL TOPICS IN OPERATIONS RESEARCH    (3-0) 3

URL: http://ie.atilim.edu.tr/~ie417

Catalog Data:

Modeling operations research problems. Dantzig-Wolfe Decomposition algorithm. Column generation method. Stochastic Processes. Markov Chains. Dynamic programming. Non-linear programming: Unconstrained and constrained non-linear algorithms.

Textbook:

Winston, W.L., Operations Research: Applications and Algorithms, 3rd edition, Duxbury Press, 1994.

References:

·         Hillier, F.S., and Lieberman, G.J., Introduction to Operations Research, 7th edition, McGraw-Hill, 2000.

·         Bazaraa, M.S., Sherali, H.D., and Shetty, C.M., Nonlinear Programming: Theory and Algorithms, 2nd edition, Wiley, 1993.

·         Taha, H.A., Operations Research, Prentice-Hall, 1997.

·         Luenberger, D., Linear and Nonlinear Programming, 2nd edition, Addison-Wesley, 1984.

Prerequisites by Topic:

Linear Algebra; basic probability concepts; Bayes’ theorem; Simplex Algorithm; duality; differential equations.

Method for Assessing Student Knowledge of Prerequisite Topics:

A prerequisite exam will be given on prerequisite topics in the first two weeks.

Goals:

Upon successful completion of this course, the student should enhance his/her analytical modeling skills and comprehend solution methodologies and techniques.

Objectives:

·         To learn how to make decisions under different environments.

·         To learn how to handle large scale IP and LP models.

·         To model and solve problems that cannot be modeled with LP or IP.

·         To use a mathematical model solving software efficiently.

Topics:

1.        Modeling operations research problems (1 week)

2.       Dantzig-Wolfe decomposition algorithm: its application to industrial engineering problems (2 weeks)

3.       Column generation method: its application to industrial engineering problems (2 weeks)

4.       Stochastic processes (3 weeks)

5.       Dynamic programming (3 weeks)

6.       Nonlinear programming (3 weeks)

Computer Usage:

Software for mathematical model solving, such as GAMS, is used throughout the course.

Laboratory Projects:

Frequent homework assignments.

Contribution to Professional Component:

1.        Mathematics and Basic Science                 0 credits

2.       Engineering Science or Design                   3 credits

3.       General Education                                     0 credits