Introduction to mathematical optimization: mathematical modeling of optimization problems, analytical and numerical optimization techniques, applications. Linear programming: simplex method, duality, integer programming; nonlinear programming: Lagrange multipliers, Karush-Kuhn-Tucker optimality conditions, convexity; approximation techniques: line search methods, gradient methods, conjugate gradient methods; variational problems; dynamic programming; optimal control.
P: MATH 209 with at least a C grade AND MATH 320 with at least a C grade or concurrent enrollment
Spring.