Ant Colony Optimization Algorithms (Paperback)


Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In computer science and operations research, the ant colony optimization algorithm is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. This algorithm is a member of ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis, the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants.

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Product Description

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In computer science and operations research, the ant colony optimization algorithm is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. This algorithm is a member of ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis, the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants.

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Product Details

General

Imprint

Brev Publishing

Country of origin

United States

Release date

March 2012

Availability

Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.

First published

March 2012

Editors

Dimensions

229 x 152 x 8mm (L x W x T)

Format

Paperback - Trade

Pages

140

ISBN-13

978-6200975751

Barcode

9786200975751

Categories

LSN

6200975752



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