Optimization in Engineering: Models and Algorithms

✍ Scribed by Ramteen Sioshansi, Antonio J. Conejo

• Publisher: Springer
• Year: 2017
• Tongue: English
• Leaves: 422
• Series: Springer optimization and its applications 120
• Edition: 1st ed.
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xv
Optimization is Ubiquitous....Pages 1-16
Linear Optimization....Pages 17-121
Mixed-Integer Linear Optimization....Pages 123-196
Nonlinear Optimization....Pages 197-285
Iterative Solution Algorithms for Nonlinear Optimization....Pages 287-336
Dynamic Optimization....Pages 337-388
Back Matter....Pages 389-412

✦ Subjects

Optimisation mathématique;Mathématiques -- Ingénierie;Génie industriel;Production -- Ingénierie