The Applied optimization methods course examines the optimization theory and techniques for practical engineering problems. Topics include classification of optimization problems, linear programming, nonlinear unconstrained optimization, nonlinear constrained optimization including inequality and equality constraints, Lagrange multiplier method, and Kuhn-Tucker conditions and solution methods, dynamic programming, random search algorithms and search methods for optimization, convex optimization methods, and application examples from different engineering disciplines.