Elective List

The course covers fundamental concepts in optimization theory. Topics will include convex analysis, linear programming, sensitivity analysis, Lagrangian duality, local optimality conditions for unconstrained and constrained nonlinear problems, and Karush-Kuhn-Tucker conditions. Optimization algorithms including the Simplex and Revised Simplex methods, steepest descent, conjugate direction and Newton's methods will be introduced