People Innovation Excellence

DETERMINISTIC OPTIMIZATION (3 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: LO1 – Identify objectives and constraints based on problem descriptions; LO2 – Create mathematical optimization models; LO3 – Apply an understanding of the techniques used to solve linear optimization models using their mathematical structure; LO4 – Use optimization software to conduct analyses and interpret the output; LO5 – Create recommendations based on solutions, analyses and model’s limitations.

Topics:

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

Published at : Updated

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