• Recognize and formulate an optimization problem by a suitable linear, convex, or combinatorial optimization model
• Apply algorithmic tools to solve the modeled problem
• Investigate  suitability of the model and efficiency of the algorithm

• Convex sets, convex functions, and convex optimization problems
• (Integer)  Linear Programming
• Characterization of local & global optima
  
• Necessary and/or sufficient conditions: Lagrange-Karush-Kuhn-Tucker
  
• Duality
• . . .
  

• Algorithms: 
  
• Simplex Method,
  
• Interior Point Methods,
  
• Ellipsoid Method
• . . .
  
• Examples and Applications

Suggested Prerequisite:  

•     CSE3101 (algorithms) or equivalent.  
  
•     Some elementary knowledge of Linear Algebra would be helpful.