Deterministic Optimization (4 Credits)
Learning Outcomes:
On successful completion of this course, student 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:
- Various Types of LP Models
- Graphical Method for two variable LP
- Sensitivity Analysis using Graphical Method
- Simplex Algorithm
- Duality Theory
- Sensitivity Analysis
- Transportation Problems
- Assignment Problems
- Transhipment Problems
- Network Models
- Modeling Integer Programming
- Solving Integer Programming
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