IEOR262A: Mathematical Programming I

Graduate student instructor for a graduate-level course covering fundamental concepts in optimization. Topics studied include convex analysis, linear programming, sensitivity analysis, Lagrangian duality, local optimality conditions for unconstrained and constrained nonlinear problems, introduction to discrete optimization. The course also studies mathematical modelling and various key optimization algorithms. Students complete theoretical and mathematical modeling exercises, as well as computational homework in AMPL.