Introduction to Applied Optimization

  • Urmila Diwekar

Part of the Springer Optimization and Its Applications book series (SOIA, volume 22)

Table of contents

  1. Front Matter
    Pages 1-20
  2. Urmila Diwekar
    Pages 1-10
  3. Urmila Diwekar
    Pages 1-29
  4. Urmila Diwekar
    Pages 1-36
  5. Urmila Diwekar
    Pages 1-48
  6. Urmila Diwekar
    Pages 1-54
  7. Urmila Diwekar
    Pages 1-36
  8. Urmila Diwekar
    Pages 1-63
  9. Back Matter
    Pages 1-13

About this book


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;
  • 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.


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

Authors and affiliations

  • Urmila Diwekar
    • 1
  1. 1.Clarendon HillsU.S.A.

Bibliographic information