"Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming" - Information and Links:

Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming - Info and Reading Options

Theory, Algorithms, Software, and Applications

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The cover of “Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming” - Open Library.

"Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming" was published by Springer US in 2002 - Boston, MA, it has 478 pages and the language of the book is English.


“Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming” Metadata:

  • Title: ➤  Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming
  • Author:
  • Language: English
  • Number of Pages: 478
  • Publisher: Springer US
  • Publish Date:
  • Publish Location: Boston, MA

“Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming” Subjects and Themes:

Edition Specifications:

  • Format: [electronic resource] :
  • Pagination: ➤  1 online resource (xxv, 478 p.)

Edition Identifiers:

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"Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming" Table Of Contents:

  • 1- Preface
  • 2- Acknowledgements
  • 3- List of Figures
  • 4- List of Tables
  • 5- 1. Introduction
  • 6- 2. Convex Extensions
  • 7- 3. Project Disaggregation
  • 8- 4. Relaxations of Factorable Programs
  • 9- 5. Domain Reduction
  • 10- 6. Node Partitioning
  • 11- 7. Implementation
  • 12- 8. Refrigerant Design Problem
  • 13- 9. The Pooling Problem
  • 14- 10. Miscellaneous Problems
  • 15- 11. GAMS/BARON: A Tutorial. A: GAMS Model for Pooling Problems
  • 16- Bibliography
  • 17- Index
  • 18- Author Index.

"Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming" Description:

The Open Library:

This book provides an insightful and comprehensive treatment of convexification and global optimization of continuous and mixed-integer nonlinear programs. Developed for students, researchers, and practitioners, the book covers theory, algorithms, software, and applications.

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