To give the students a working knowledge of optimization theory and methods and to equip the students with sufficient backround for further study of advanced topics in optimization.

Introduction to Optimization, Convex Analysis, Optimality Conditions and Duality, Unconstrained Problems, Problems with Inequality Constraints, Problems with Inequality and Equality Constraints, Second Order-Necessary and Sufficient Optimality Conditions for Constrained Problems, Lagrangian Duality and Saddle Point Optimality Conditions. Algorithms and Their Convergence, Optimization in Application Area.