Theory and use of numerical design optimization methods. Problem formulation, practical application, and results analysis. Unconstrained nonlinear problems, constrained linear and nonlinear problems, and multi-objective optimization. Graduate students will do additional work in surrogate models and optimizing under uncertainty. Extensive use of Matlab functions and programming. Enrollment Requirements: Prereq: MAT 485.