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Implemented in a classroom setting or used for independent study
Self-contained chapters that include problem sets and exercises
Provides a thorough introduction to applied optimization with unique applications
Introduces a number of important results in the field
Includes an extensive bibliography at the end of each chapter
Solutions manual available upon adoptions
This text presents amulti-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.
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.
Content Level »Graduate
Keywords »Theorie - algorithms - development - global optimization - linear optimization - multi-objective optimization - nonlinear optimization - optimization - programming