The wide scope of optimization mandates extensive interaction between various disciplines in the development of the methods and algorithms, and in their fruitful application to real-world problems. This book presents a discipline-independent view of optimization, providing opportunities for students to identify and apply algorithms, methods, and tools from the diverse areas of optimization to their own fields without getting into too much detail about the underlying theories. The second edition of this book includes two new chapters: a chapter on global optimization and a real-world case study that uses principles from each chapter. Key Features: (1) Provides self-contained chapters, including problem sets and exercises; (2) Introduces applied optimization with several unique applications, i.e., hazardous waste blending problem; (3) Explores a number or important methods, i.e., the simplex method, weighting method, constraint method, and goal programming method; (4) Explores several different types of optimization, i.e., discrete, global, multi-objective, and dynamic optimization; (5) Includes an extensive bibliography at the end of each chapter. This book is intended for a variety of scientists, engineers, researchers, and advanced students interested in applied optimization.