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Stochastic Local Search: Foundations and Applications (The Morgan Kaufmann Series in Artificial Intelligence) - Tapa dura

Libro 14 de 14: The Morgan Kaufmann Series in Artificial Intelligence

Hoos, Holger H.; Stützle, Thomas

 
9781558608726: Stochastic Local Search: Foundations and Applications (The Morgan Kaufmann Series in Artificial Intelligence)
Tapa dura
ISBN 10: 1558608729 ISBN 13: 9781558608726
Editorial: Morgan Kaufmann Publishers In, 2004

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

By Holger Hoos and Thomas Stutzle

De la contraportada

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.|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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Morgan Kaufmann Publishers In
Año de publicación
2004
Idioma
Inglés
ISBN 10 
1558608729
ISBN 13 
9781558608726
Encuadernación
Tapa dura
Número de páginas
658
Contacto del fabricante
no disponible
Persona responsable
Barbara Criscuolo
b.criscuolo@lswr.it

Via Spadolini, 7
Milano
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Italia