Title
Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice (International Series in O,Used
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Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, highlevel algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments.
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- Q: What is the main focus of 'Potential Function Methods for Approximately Solving Linear Programming Problems'? A: The book focuses on breaking new ground in linear programming theory, exploring approximation algorithms for classes of linear programming problems.
- Q: Who is the author of this book? A: The author is Daniel Bienstock, a recognized expert in optimization research.
- Q: What topics are covered in this book? A: The book covers linear and integer programming, numerical analysis, and computational architectures that aid in algorithm design.
- Q: What is the condition of the book being sold? A: The book is listed as 'New', ensuring it is in pristine condition.
- Q: How many pages does the book contain? A: The book contains a total of 130 pages.
- Q: What type of binding does this book have? A: The book is bound in hardcover, providing durability and a professional appearance.
- Q: When was this book published? A: The book was published on August 31, 2002.
- Q: What is the significance of the research discussed in the book? A: The research represents a new body of work in optimization, focusing on developing effective approximation algorithms with strong theoretical foundations.
- Q: Is this book suitable for beginners in linear programming? A: While the book provides valuable insights, it is recommended for readers with some foundational knowledge in linear programming and optimization theory.
- Q: Does this book include practical examples of algorithms? A: Yes, the book examines various algorithms, starting from early examples to the latest theoretical and computational advancements.