Textbook

• Winston, Wayne L. Introduction to Mathematical Programming: Applications and Algorithms, 2^nd edition. Duxbury Press, 1995.

References

• Rardin, Ronald L., Optimization in Operations Research, Prentice Hall, 1997.
• Hillier, Frederick H. and Lieberman, Gerald, Introduction to Operations Research, McGraw-Hill, 1995.
• Taha, Hamdi A., Operations Research: An Introduction, Prentice Hall, 1996.

This course gives an introduction to deterministic operations research models. It provides

• an introduction to some widely used quantitative models, such as linear and integer programming and network flows;
• an explanation of the mathematical ideas behind these widely used models;
• an introduction to and hands-on experience with software such as Lindo for solving such models;
• examples of real-world applications;

• developing skills in modeling and solving real world business and engineering problems;
• understanding the issues involved in model assumptions, complexity and solution effort;
• providing a formal quantitative approach to problem solving; and
• to provide an intuition for managerial situations where a quantitative approach is appropriate.

1. Introduction to Optimization
2. Model Formulation: Constructing a model (components, assumptions), examples.
3. Linear Programming: Graphical solution, characterization of optimal solutions, simplex method, sensitivity analysis, duality, post-optimization changes to the problem.
4. Network Problems: Model formulation, special cases (transportation, assignment, shortest path, minimum spanning tree), special case solution methods, "hard" problems.
5. Integer Programming: Modeling using integer variables, solution methods (e.g., branch-and-bound).
6. Nonlinear Programming: Easy vs. hard problems (Convexity), Economic Order Quantity (EOQ), Regression (squared and absolute error)

Homework: All homework assignments will be required. Some homework assignments might be based on case studies. Students can discuss the assignments, but every student must turn in his/her own written solutions in his/her own words. Homework is meant to be a learning tool. If you are having difficulty, find help right away – don’t wait until you fall even further behind! Good sources of help are fellow students, teaching assistants, and I.

Midterm Exams: The midterm exams will be held on or about October 3^rd and November 16^th. Exact dates will be announced closer to each exam. In-class exams will be closed book and must be done individually.

Final Exam: The final exam will be held from11:30am-2:20pm on December 11^th. Please check http://www.oscarweb.gatech.edu/fall/oscar/finals.html for possible changes in the schedule.

Grading: Homework assignments will account for 20% of your total grade. Depending on their length and difficulty, homework assignments might carry different weights. Each midterm exam will contribute 25% and the final exam will contribute 30% to your final grade.
 
 

USEFUL LINKS

• Remote Interactive Optimization Testbed (RIOT) from U.C. Berkeley. This site contains and introduction and Java applets for solving various optimization problems such as clinching and elimination in major league baseball and basketball, financial portfolio optimization, vehicle routing and scheduling.
• A tutorial on Integer Programming (by Professor Michael Trick from Carnegie Mellon University)
• Network optimization (by Professor Michael Trick)
• A tutorial on Dynamic Programming (by Professor Michael Trick)