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Stochastic Local Search : Foundations & Applications (The Morgan Kaufmann Series in Artificial Intelligence) - Hardcover

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Synopsis

Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics.

Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool.

  • Provides the first unified view of the field
  • Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications
  • Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms
  • A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms

"synopsis" may belong to another edition of this title.

Book Description

This books provides the first unified view of the field

From the Back Cover

Stochastic local search is a powerful search technique for solving a wide range of combinatorial problems. If you only want to read one book on this important topic, you should read Hoos and Stützle's text.
―Toby Walsh, Cork Constraint Computation Centre, University College Cork

This book provides remarkable coverage and synthesis of the recent explosion of work on randomized local search algorithms. It will serve as a good textbook for classes on heuristic search and metaheuristics as well as a central reference for researchers.
― David L. Woodruff, University of California, Davis

Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics.

Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool.

Features
*Provides the first unified view of the field.
*Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications.
*Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms.
*A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms.

"About this title" may belong to another edition of this title.

  • PublisherMorgan Kaufmann
  • Publication date2004
  • ISBN 10 1558608729
  • ISBN 13 9781558608726
  • BindingHardcover
  • LanguageEnglish
  • Edition number1
  • Number of pages658
  • Rating
    • 4.11 out of 5 stars
      9 ratings by Goodreads

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