Sioshansi R., Conejo A.J. Optimization in Engineering: Models and Algorithms

Springer International Publishing AG, 2017. — 422 p. — (Springer Optimization and Its Applications 120) — ISBN: 3319567675.This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas.
Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems.
The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.Optimization is Ubiquitous
Linear Optimization
Mixed-Integer Linear Optimization
Nonlinear Optimization
Iterative Solution Algorithms for Nonlinear Optimization
Dynamic Optimization
Appendixes
Taylor Approximations and Definite Matrices
Convexity