This course provides an introduction to optimization. It is composed of four modules. In Module I, mathematical preliminaries are developed. In Module II, foundation of vector space, function convexity and unconstrained optimization are introduced. In Module III, Linear Programming is discussed at a greater depth than in introductory Operations Research (OR) courses, with an emphasis on its geometric interpretation. Students develop solid knowledge of Linear Programming and its software tools and applications. In Module IV, the knowledge of the first three modules is extended to Integer Programming, Nonlinear Programming and Dynamic Programming at an introductory level to broaden the knowledge of optimization. In each module, application-oriented models are discussed.
This course is intended for Masters and PhD graduate students with prior knowledge of introductory OR and Calculus.