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- Includes problem sets and exercises
- Introduces applied optimization with unique applications
- Solutions manual available upon adoptions
- Request lecturer material: sn.pub/lecturer-material
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 22)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
Intended for advanced undergraduate/graduate students as well as scientists and engineers, this textbook presents a multi-disciplinary view of optimization, providing a thorough examination of algorithms, methods, techniques, and tools from diverse areas of optimization. Linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control, and stochastic optimal control are introduced in each self-contained chapter, with exercises, examples, and case studies, the true gems of this text. This third edition includes additional content in each chapter designed to clarify or enhance the exposition, and update methodologies and solutions. A new real-world case study related to sustainability is added in Chapters 2—7. GAMS, AIMMS, and MATLAB® files of case studies for Chapters 2, 3, 4, 5, and 7 are freely accessible electronically as extra source materials. A solutions manual is available to instructors who adopt the textbook for their course.
From the reviews:
This work is definitely a welcome addition to the existing optimization literature, given its emphasis on modeling and solution practice, as well as its ‘user-friendly’ style of exposition. — János D. Pintér, European Journal of Operations Research, Vol. 177, 2007
Urmila Diwekar’s book on applied optimization is one of the few books on the subject that combines impressive breadth of coverage with delightful readability. In her exposition of concepts and algorithms in the major areas of optimization, she always goes to the heart of the matter and illustrates her explanations with simple diagrams and numerical examples. Graduate and undergraduate students, who constitute part of the target audience, should find this a very useful book. — Jamshed A. Modi, Interfaces, Vol.36 (1), 2006
Optimization is a rich field with a strong history; this book nicely introduces both, moving from very introductory material to challenging techniques toward the end … Examples range from quite simplistic through realistic difficult scheduling problems. Some examples resurface in different chapter with twists to demonstrate how different techniques are required for differing data and constraints. — CHOICE, September 2004
Keywords
- algorithms
- global optimization
- linear optimization
- multi-objective optimization
- nonlinear optimization
- optimization
- programming
- Linear Programming
- Nonlinear Programming
- Discrete Optimization
- Optimization under Uncertainty
- Multi-objective Optimization
- Optimal Control
- Applied Optimization
- stochastic optimal control
- GAMS
Authors and Affiliations
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Vishwamitra Research Institute, Crystal Lake, USA
Urmila M. Diwekar
About the author
Bibliographic Information
Book Title: Introduction to Applied Optimization
Authors: Urmila M. Diwekar
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-030-55404-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-55403-3Published: 30 October 2020
Softcover ISBN: 978-3-030-55406-4Published: 30 October 2021
eBook ISBN: 978-3-030-55404-0Published: 29 October 2020
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 3
Number of Pages: XXIX, 358
Number of Illustrations: 92 b/w illustrations, 20 illustrations in colour
Topics: Optimization, Mathematical and Computational Engineering, Operations Research/Decision Theory, Calculus of Variations and Optimal Control; Optimization, Systems Theory, Control