Description

Book Synopsis
  • 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.



Table of Contents
1. Introduction.- 2. Linear Programming.- 3. Nonlinear Programming.-4. Discrete Optimization.- 5. Optimization Under Uncertainty.- 6. Multiobjective Optimization.- 7.Optimal Control and Dynamic Optimization.- Index.

Introduction to Applied Optimization

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    Order before 4pm tomorrow for delivery by Tue 9 Jun 2026.

    A Hardback by Urmila M. Diwekar

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      View other formats and editions of Introduction to Applied Optimization by Urmila M. Diwekar

      Publisher: Springer Nature Switzerland AG
      Publication Date: 30/10/2020
      ISBN13: 9783030554033, 978-3030554033
      ISBN10: 3030554031

      Description

      Book Synopsis
      • 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.



      Table of Contents
      1. Introduction.- 2. Linear Programming.- 3. Nonlinear Programming.-4. Discrete Optimization.- 5. Optimization Under Uncertainty.- 6. Multiobjective Optimization.- 7.Optimal Control and Dynamic Optimization.- Index.

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