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Mathematics | Introduction to Applied Optimization

Introduction to Applied Optimization

Diwekar, Urmila

2nd ed. 2008, XXV, 291 p.

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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 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.

Content Level » Graduate

Keywords » Theorie - algorithms - development - global optimization - linear optimization - multi-objective optimization - nonlinear optimization - optimization - programming

Related subjects » Applications - Business & Management - Computational Intelligence and Complexity - Industrial Chemistry and Chemical Engineering - Mathematics

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