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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    A Hardback by Urmila M. Diwekar

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      Publisher: Springer Nature Switzerland AG
      Publication Date: 30/10/2020
      ISBN13: 9783030554033, 978-3030554033
      ISBN10: 3030554031
      Also in:
      Business, Finance & Law Operational research Mathematics Optimization Technology, Engineering & Agriculture Maths for engineers

      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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