This course provides an introduction to optimization. It is designed to develop mathematical sophistication that is required in research work in production systems engineering and industrial economics. It covers deterministic models and methods that are useful in solving problems of resource configuration, portfolio and mix planning, supply chain control, scenario-based planning, risk management, operation scheduling, and policy design. It is composed of three parts. In the first part, Linear Programming is discussed at a greater depth than in introductory OR courses, with an emphasis on its geometric interpretation. About half of the semester is devoted to equip students with solid knowledge about Linear Programming and its software tools and applications. In the second part, the knowledge on Linear Programming will be extended to Non-linear Programming, Integer Programming, and Stochastic Linear Programming. In the third part, we will discuss dynamic optimization and optimal control and their application to supply chain control and policy design.