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Constraint-Based Local Search [Englisch] [Taschenbuch]

Pascal Van Hentenryck , Laurent Michel

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Kurzbeschreibung

30. September 2009
The ubiquity of combinatorial optimization problems in our society is illustrated by the novel application areas for optimization technology, which range from supply chain management to sports tournament scheduling. Over the last two decades, constraint programming has emerged as a fundamental methodology to solve a variety of combinatorial problems, and rich constraint programming languages have been developed for expressing and combining constraints and specifying search procedures at a high level of abstraction. Local search approaches to combinatorial optimization are able to isolate optimal or near-optimal solutions within reasonable time constraints.This book introduces a method for solving combinatorial optimization problems that combines constraint programming and local search, using constraints to describe and control local search, and a programming language, COMET, that supports both modeling and search abstractions in the spirit of constraint programming.After an overview of local search including neighborhoods, heuristics, and metaheuristics, the book presents the architecture and modeling and search components of constraint-based local search and describes how constraint-based local search is supported in COMET. The book describes a variety of applications, arranged by meta-heuristics. It presents scheduling applications, along with the background necessary to understand these challenging problems. The book also includes a number of satisfiability problems, illustrating the ability of constraint-based local search approaches to cope with both satisfiability and optimization problems in a uniform fashion.

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"Constraint-Based Local Search presents a powerful new programming language paradigm for combinatorial optimization, uniting the power of local search with the declarativeness of constraint programming. This book will become an important reference for students and practitioners of combinatorial optimization." Andrew J. Davenport, IBM T. J. Watson Research Center "*Constraint-Based Local Search* presents a powerful new programming language paradigm for combinatorial optimization, uniting the power of local search with the declarativeness of constraint programming. This book will become an important reference for students and practitioners of combinatorial optimization."--Andrew J. Davenport, IBM T.J. Watson Research Center

Synopsis

Introducing a method for solving combinatorial optimisation problems that combines the techniques of constraint programming and local search. The ubiquity of combinatorial optimisation problems in our society is illustrated by the novel application areas for optimisation technology, which range from supply chain management to sports tournament scheduling. Over the last two decades, constraint programming has emerged as a fundamental methodology to solve a variety of combinatorial problems, and rich constraint programming languages have been developed for expressing and combining constraints and specifying search procedures at a high level of abstraction. Local search approaches to combinatorial optimisation are able to isolate optimal or near-optimal solutions within reasonable time constraints. This book introduces a method for solving combinatorial optimisation problems that combines constraint programming and local search, using constraints to describe and control local search, and a programming language, COMET, that supports both modelling and search abstractions in the spirit of constraint programming.

After an overview of local search including neighbourhoods, heuristics, and metaheuristics, the book presents the architecture and modelling and search components of constraint-based local search and describes how constraint-based local search is supported in COMET. The book describes a variety of applications, arranged by meta-heuristics. It presents scheduling applications, along with the background necessary to understand these challenging problems. The book also includes a number of satisfiability problems, illustrating the ability of constraint-based local search approaches to cope with both satisfiability and optimisation problems in a uniform fashion. -- Dieser Text bezieht sich auf eine vergriffene oder nicht verfügbare Ausgabe dieses Titels.


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Amazon.com: 3.2 von 5 Sternen  4 Rezensionen
1 von 1 Kunden fanden die folgende Rezension hilfreich
2.0 von 5 Sternen A 400-page infomercial 18. Februar 2012
Von John C. - Veröffentlicht auf Amazon.com
Format:Taschenbuch
This book has some informative sections on techniques for solving complex optimization problems, but devolves into a 400-page ad for the author's commercial software tool, COMET. You are better off just downloading the COMET tutorial for free if you are interested in this software.
4 von 6 Kunden fanden die folgende Rezension hilfreich
1.0 von 5 Sternen Software manual 1. Juli 2009
Von lew - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
This book is manual for commercial software named COMET. COMET is distributed by company DYNADEC. Athough it is possible to get 30 days evaluation copy of COMET, there is no information on company web page regarding the cost of the software. The book is completely dependent on COMET and there is very little general information, both about local search and constraint programming. All examples are written in COMET language

Can be useful if the reader plans to purchase COMET, not very useful otherwise
5.0 von 5 Sternen A Great Introduction to CBLS with many Examples 15. April 2013
Von Carleton Coffrin - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Verifizierter Kauf
In the interest of full disclosure, I have been a student of both the authors of this text.

This book introduces the core ideas of Constraint-Based Local Search (CBLS) both in modeling and in search. It provides many examples to illustrate the core concepts. The examples range from classic puzzles including Magic Square, Magic Series, All-Interval Series, and N-Queens to realistic decision problems such as Frequency Allocation and Jobshop Scheduling. This book will teach you the "art" of solving problems with CBLS. It will not teach you how to implement your own CBLS solver. Readers seeking that knowledge should review the Ph.D. thesis of the book's author, Laurent Michel ("Localizer: A Modeling Language for Local Search").
1 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen A great book for teaching Local Search 5. Juli 2009
Von Yves Deville - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
I am using CBLS book for several years at my local search class. It introduces Local Search, and shows how Local Search can be used for solving numerous classes of problems. All the standard local search techniques are described. This book also introduces the Comet language, a new programming language with embedded mecanisms for local search. This language is free for academic purposes.

The students had fun playing with Comet; it allows to quickly program and compare local search techniques.
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