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

The Travelling Salesman Problem (more politically correctly called the Travelling Salesperson Problem)(How about we call it the TSP?) is a common real world problem. The problem is simplely stated: How do you find the shortest path for a travelling sales\_\_\_\_\_ to drive as he visits a series of customers. If you're just running a few errands it's easy enough. If you're going to the supermarket, the post office, the dry cleaners, and the gas station, it's pretty easy to determine the shortest path. But then you add constraints, nearly out of gas, go to gas station first. Buying ice cream at the super market, better make it the last stop. This is a real world problem. It is faced every day by delivery companies like the post office and air freight companies who spend huge amounts of fuel flying jet freighters around the world -- where do you put a hub, how do you schedule everything to come together. FedEx solved this problem by running everything through Memphis. This works really well for a package going from New York to LA. It works less well for a package going from Manhattan to the Bronx. And if the package is going from London to Manchester .... The computation of this and similar problems fall into the general category of Stochastic Local Search. And this book is the first to offer a systematic and unified treatment of SLS. Before this there were a series of technical papers, magazine articles and chapters in more general texts. The book provides the first unified view of the entire field and offers an extensive review of state-of-the-art algorithms and their applications. A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating the algorithms. 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

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. 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 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. 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 "Hoos and Stutzle offer the first systematic and unified treatment of SLS algorithms. In this 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."--BOOK JACKET. Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application This introductory chapter provides the background and motivation for studying stochastic local search algorithms for combinatorial problems.