Introduction to Applied Optimization
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Beschreibung
This text presents a multi-disciplined view of optimization, providing students and researchers with a thorough examination of algorithms, methods, and tools from diverse areas of optimization without introducing excessive theoretical detail. This second edition includes additional topics, including global optimization and a real-world case study using important concepts from each chapter.
Key Features:
Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting;
Introduces applied optimization to the hazardous waste blending problem;
Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control;
Includes an extensive bibliography at the end of each chapter and an index;
GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8;
Solutions manual available upon adoptions.
Introduction to Applied Optimization is intended for advanced undergraduate and graduate students and will benefit scientists from diverse areas, including engineers.
Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting;
Introduces applied optimization to the hazardous waste blending problem;
Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control;
Includes an extensive bibliography at the end of each chapter and an index;
GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8;
Solutions manual available upon adoptions.
Introduction to Applied Optimization is intended for advanced undergraduate and graduate students and will benefit scientists from diverse areas, including engineers.
Autor*in
Urmila Diwekar
Themen in »Introduction to Applied Optimization«
algorithms combinatorial optimization control discrete optimization global optimization linear optimization multi-objective optimization network nonlinear optimization optimal control optimization programming separation process uncertainty
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From the reviews:
"The book is well written and the presentation is rigorous and self-contained. The book will be of interest to researchers in various fields as well as undergraduate and graduate students in engineering sciences, management science, and decision science." (I. M. Stancu-Minasian, Zentralblatt MATH, Vol. 1043 (18), 2004)
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