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Unformatted text preview: IE406: Introduction to Mathematical Programming Syllabus Dr. Ted Ralphs Fall 2007 1 Miscellaneous Course Information Instructor: Dr. Ted Ralphs Office: 473 Mohler Lab Phone: 8-4784 E-mail: tkr2 Office Hours: MW 4:00-5:00 or by appointment Web page: http://www.lehigh.edu/tkr2 Course web page: http://www.lehigh.edu/tkr2/teaching/ie406/ Course meeting time: MW 6:00-7:15 2 Description of Course This course will be an introduction to mathematical programming, with an emphasis on techniques for the solution and analysis of deterministic linear models. The primary types of models to be addressed will be linear programming, network flow, and integer linear programming. However, the course will touch on more complex models, such as those incorporating nonlinear constraints or uncertainty. The main emphasis will be on solution techniques and on analysis of the underlying mathematical structure of these models. As a supporting theme, the course will also emphasize effective modeling techniques, the use of modeling languages, such as AMPL, and the use of com- mercial solvers. 3 Course Objectives The goals of this course are for students to: 1. Improve their ability to rigorously prove mathematical statements. 2. Cultivate an ability to analyze the structure of and mathematically model various complex system occurring in industrial applications. 3. Develop knowledge of the mathematical structure of the most commonly used deterministic linear optimization models. 1 4. Develop an understanding of the techniques used to solve linear optimization models using their mathematical structure. 5. Develop an understanding of the use of modeling languages for expressing and solving opti- mization models. 6. Develop knowledge of existing solvers for linear optimization. 4 General Course Requirements 4.1 Prerequisites I expect you to have a good undergraduate mathematics background, especially in linear algebra. I expect some familiarity with logic and proof techniques, as well as basic knowledge of computer programming. Experience with mathematical modeling is a plus. 4.2 Recommended Primary Text D. Bertsimas and J.N. Tsitsiklis, Introduction to Linear Optimization , Athena Scientific (1997). 4.3 Reading There will be required readings associated with each lecture. Most readings will be from the course text, but students are encouraged to seek supplementary material. Links to supplementary reading material can be accessed from the course page. 4.4 Lectures You are expected to attend and participate in the lectures. Part of the grade will be determined by overall class participation. Lecture materials will be available for reference before the lecture on the course web page....
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- Spring '08