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The book "Stochastic Local Search --- Foundations & Applications" by
H. H. Hoos and T. Stuetzle has now been published by
Morgan Kaufmann Publishers, an imprint of Elsevier.
Table of Contents
==================
Prologue
Part I. Foundations
1. Introduction
2. SLS Methods
3. Generalised Local Search Machines
4. Empirical Analysis of SLS Algorithms
5. Search Space Structure and SLS Performance
Part II. Applications
6. SAT and Constraint Satisfaction
7. MAX-SAT and MAX-CSP
8. Travelling Salesman Problems
9. Scheduling Problems
10. Other Combinatorial Problems
Epilogue
Glossary
Short description
==================
Stochastic local search (SLS) methods, such as Iterative Improvement,
Simulated Annealing, Tabu Search, Iterated Local Search, Ant Colony
Optimisation and Evolutionary Algorithms (also known as
Metaheuristics) 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 Stuetzle 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.
The book has 672 pages including a 38-page glossary, 117 figures and
100 exercises. Supplementary material is provided at the web site
www.sls-book.net.
More information
=================
www.sls-book.net or http://books.elsevier.com/mk/?isbn=1558608729
How to order
=============
Order direct from Morgan Kaufmann Publishers and recieve 20% off.
To order the book from the US or Canada (discount code 78127), go here:
http://books.elsevier.com/mk/?isbn=1558608729&srccode=78127
To order from anywhere else in the world (discount code ABR5), go here:
http://books.elsevier.com/mk?isbn=1558608729&scrcode=ABR5
Reviews
========
Hoos and Stuetzle, two major players in the field, provide us with an
excellent overview of stochastic local search. If you are looking for
a book that covers all the major metaheuristics, gives you insight
into their working, and guides you in their application to a wide set
of combinatorial optimization problems, this is the book.
- Marco Dorigo, Universite Libre de Bruxelles
Stochastic Local Search: Foundations and Applications provides an
original and synthetic presentation of a large class of algorithms
more commonly known as metaheuristics. Over the last 20 years, these
methods have become extremely popular, often representing the only
practical approach for tackling so many of the hard combinatorial
problems that are encountered in real-life applications. Hoos and
Stuetzle's treatment of the topic is comprehensive and covers a variety
of techniques, including simulated annealing, tabu search, genetic
algorithms and ant colony optimization, but a main feature of the book
is its proposal of a most welcome unifying framework for describing
and analyzing the various methods.
- Michel Gendreau, Universite de Montreal
Local search algorithms are often the most practical approach to
solving constraint satisfaction and optimization problems that admit
no fast deterministic solution. This book is full of information and
insights that would be invaluable for both researchers and
practitioners.
- Henry Kautz, University of Washington
This extensive book provides an authoritative and detailed exposition
for novices and experts alike who need to tackle difficult decision or
combinatorial optimization problems. The chapters span fundamental
theoretical questions such as, "When and why do heuristics work well?"
but also more applied aspects involving, for instance, the comparison
of very different algorithms. The authors are university faculty
members and leading players in their research fields; our communities
will enjoy in particular their book's' valuable teaching material and
a "complete" bibliography of the state of the art for the field.
- Olivier Martin, Universite Paris-Sud, Orsay
The authors provide a lucid and comprehensive introduction to the
large body of work on stochastic local search methods for solving
combinatorial problems. The text also covers a series of carefully
executed empirical studies that provide significant further insights
into the performance of such methods and show the value of an
empirical scientific methodology in the study of algorithms. An
excellent overview of the wide range of applications of stochastic
local search methods is included.
- Bart Selman, Cornell University
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 Stuetzle's. It
is a comprehensive and informative survey of the field that will equip
you with the tools and understanding to use stochastic local search to
solve the problems you come across.
- Toby Walsh, University of New South Wales, Sydney
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. The book provides a
unification of a broad spectrum of methods that enables concise,
highly readable descriptions of theoretical and experimental results.
- David L. Woodruff, University of California, Davis
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