Logic-based methods for optimization. Combining optimization and constraint satisfaction.

*(English)*Zbl 0974.90001
Wiley-Interscience Series in Discrete Mathematics and Optimization. Chichester: Wiley. viii, 495 p. (2000).

From the preface: This book is for readers who wish to solve optimization problems more effectively, or to integrate optimization and constraint satisfaction. It accomplishes both tasks by analyzing and extending the role of logic in optimization.

The book is written for people with background in either optimization or constraint satisfaction, but not necessarily both. For those new to constraint satisfaction techniques, it contains three tutorial chapters on these and constraint programming. For those with limited background in optimization, it provides examples and elementary explanations of the relevant optimization methods.

The book is for practitioners as well as theorists. About two-thirds of the book presents techniques and modeling frameworks that are essentially ready for implementation. Some are already successfully implemented. The practitioner should therefore find the book of immediate value.

The remainder of the book digs a little deeper. It suggests unproven ideas that could require further development before application.

The book is also suitable for a graduate seminar involving students trained in optimization or constraint satisfaction/constraint programming. The introductory chapter outlines some possible study plans.

The book is written for people with background in either optimization or constraint satisfaction, but not necessarily both. For those new to constraint satisfaction techniques, it contains three tutorial chapters on these and constraint programming. For those with limited background in optimization, it provides examples and elementary explanations of the relevant optimization methods.

The book is for practitioners as well as theorists. About two-thirds of the book presents techniques and modeling frameworks that are essentially ready for implementation. Some are already successfully implemented. The practitioner should therefore find the book of immediate value.

The remainder of the book digs a little deeper. It suggests unproven ideas that could require further development before application.

The book is also suitable for a graduate seminar involving students trained in optimization or constraint satisfaction/constraint programming. The introductory chapter outlines some possible study plans.

Reviewer: Juan Manuel Otero (Habana)

##### MSC:

90-02 | Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming |

03B35 | Mechanization of proofs and logical operations |

68T20 | Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) |

90C27 | Combinatorial optimization |

90C59 | Approximation methods and heuristics in mathematical programming |