By
Holger H. Hoos, The University of British Columbia, Canada
Thomas Stützle, Darmstadt University of Technology, Germany
Description
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.
Audience:
Academic and industry researchers in CS, AI, operations research, and engineering (as an introduction to and/or overview of the field
or as a reference text); practitioners who need to solve combinatorial problems for practical applications.
