Mlsd Technique Overview 16888 E77 Steepest Descent UNCONSTRAINED Conjugate Gradient Quasi-Newton Newton Simplex-linear CONSTRAINED SLP-linear SQP-nonlinear, expensive, common in engineering applications Exterior Penalty-nonlinear, discontinuous design spaces Interior Penalty-nonlinear Generalized reduced gradient- nonlinear Method of feasible directions nonlinear Mixed Integer Programming C Massachusetts Institute of Technology - Prof de Weck and Prof Willcox Engineering Systems Division and Dept of Aeronautics and Astronautics6 © Massachusetts Institute of Technology - Prof. de Weck and Prof. Willcox Engineering Systems Division and Dept. of Aeronautics and Astronautics Technique Overview Technique Overview Steepest Descent Conjugate Gradient Quasi-Newton Newton Simplex – linear SLP – linear SQP – nonlinear, expensive, common in engineering applications Exterior Penalty – nonlinear, discontinuous design spaces Interior Penalty – nonlinear Generalized Reduced Gradient – nonlinear Method of Feasible Directions – nonlinear Mixed Integer Programming UNCONSTRAINED CONSTRAINED