Ant Colony Optimization and Constraint Programming

Nonfiction, Computers, Programming, Software Development
Cover of the book Ant Colony Optimization and Constraint Programming by Christine Solnon, Wiley
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Author: Christine Solnon ISBN: 9781118618899
Publisher: Wiley Publication: March 4, 2013
Imprint: Wiley-ISTE Language: English
Author: Christine Solnon
ISBN: 9781118618899
Publisher: Wiley
Publication: March 4, 2013
Imprint: Wiley-ISTE
Language: English

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts.

The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search approaches and metaheuristics, and shows how they can be integrated within constraint programming languages.

The second part describes the ant colony optimization metaheuristic and illustrates its capabilities on different constraint satisfaction problems.
The third part shows how the ant colony may be integrated within a constraint programming language, thus combining the expressive power of constraint programming languages, to describe problems in a declarative way, and the solving power of ant colony optimization to efficiently solve these problems.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts.

The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search approaches and metaheuristics, and shows how they can be integrated within constraint programming languages.

The second part describes the ant colony optimization metaheuristic and illustrates its capabilities on different constraint satisfaction problems.
The third part shows how the ant colony may be integrated within a constraint programming language, thus combining the expressive power of constraint programming languages, to describe problems in a declarative way, and the solving power of ant colony optimization to efficiently solve these problems.

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