DETERMINISTIC OPTIMIZATION (4 Credits)

Learning Outcomes:

At the end of this course, students will be able to:Identify objectives and constraints based on problem descriptions; Create mathematical optimization models; Select and work through proper solution techniques; Use optimization software to conduct analyses and interpret the output; Express recommendations based on solutions, analyses and model’s limitations.

Topics:

1. Various Types of LP Models;
2. Graphical Method for two variable LP;
3. Sensitivity Analysis using Graphical Method;
4. Simplex Algorithm;
5. Duality Theory;
6. Sensitivity Analysis;
7. Transportation Problems;
8. Assignment Problems;
9. Transhipment Problems;
10. Network Models;
11. Modeling Integer Programming;
12. Solving Integer Programming.