Overview
- Offers a problem-solving approach and a large number of illustrative examples leading to a step-by-step formulation and solving of optimization problems
- Discussions are based on real-world examples and case studies
- Clarity of presentation maintains mathematical rigor
- Optimization textbook with broad appeal expressly for engineering upper-undergraduates/graduate students
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 120)
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About this book
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.
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Keywords
- linear programming
- modeling GAMS
- optimization energy
- optimization engineering
- optimization undergraduate engineering
- optimization undergraduate textbook
- graduate textbook industrial engineering
- dynamic optimization problem
- linear optimization problem
- mixed-integer optimization
- nonlinear optimization problem
- duality theory
- Taylor approximation
Table of contents (6 chapters)
Authors and Affiliations
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Bibliographic Information
Book Title: Optimization in Engineering
Book Subtitle: Models and Algorithms
Authors: Ramteen Sioshansi, Antonio J. Conejo
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-319-56769-3
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-56767-9Published: 03 July 2017
Softcover ISBN: 978-3-319-85996-5Published: 10 August 2018
eBook ISBN: 978-3-319-56769-3Published: 24 June 2017
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: XV, 412
Number of Illustrations: 45 b/w illustrations, 26 illustrations in colour