People Innovation Excellence

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.

 


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