Courses

• 36-701      Intermediate Probability
• 36-753/54 Probability Theory and Stochastic Processes
• 47-830      Integer Programming
• 47-834      Linear Programming
• 47-835      Graph Theory
• 47-840      Dynamic Programming
• 47-936      Convex Polytopes
• 47-831      Advanced Integer Programming
• 47-832      Nonlinear Programming
• 47-836      Networks and Matchings
• 47-844      Optimization, Logical and Constraint Satisfaction:
                     This course develops integer programming, constraint programming, and global optimization from a unified point of view that sees these fields as special cases of a single problem-solving technology. The focus is on methods used in major general-purpose solvers. Topics covered include constraint propagation, filtering and relaxation for global constraints,
  domain consistency, cutting planes, convexification, branch-infer-and-relax methods, logic-based Benders methods, and modeling. The course presupposes no knowledge of optimization other than linear programming.
   
• 47-846      Analysis and Heuristics
• 47-848      Network Design Algorithms
• 47-856      Theory and Algorithms for Linear Programming
• 47-860      Convex Analysis