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 Stutzle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the...

Collecting work presented at the 9th Metaheuristics International Conference (2011), this book covers theoretical properties and performance guarantees, configuration of metaheuristic algorithms, combining metaheuristics and other algorithmic methods and more.