Ant Colony Optimization (Bradford Books)

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9780262042192: Ant Colony Optimization (Bradford Books)
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"Inspired by the remarkable ability of social insects to solve problems, Dorigo and Stutzle introduce highly creative new technological design principles for seeking optimized solutions to extremely difficult real-world problems, such as network routing and task scheduling. This is essential reading not only for those working in artificial intelligence and optimization, but for all of us who find the interface between biology and technology fascinating."--Iain D. Couzin, University of Oxford

Reseña del editor:

The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses.The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.

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Dorigo, Marco; Stutzle, Thomas; Sttzle, Thomas
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Dorigo, Marco; Stützle, Thomas
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Descripción A Bradford Book. Estado de conservación: New. 0262042193 This is an International Edition. Brand New, Hardcover, Delivery within 6-14 business days, Similar Contents as U.S Edition, ISBN and Cover design may differ, printed in Black & White. Choose Expedited shipping for delivery within 3-8 business days. We do not ship to PO Box, APO , FPO Address. In some instances, subjects such as Management, Accounting, Finance may have different end chapter case studies and exercises. International Edition Textbooks may bear a label "Not for sale in the U.S. or Canada" and "Content may different from U.S. Edition" - printed only to discourage U.S. students from obtaining an affordable copy. The U.S. Supreme Court has asserted your right to purchase international editions, and ruled on this issue. Access code/CD is not provided with these editions , unless specified. We may ship the books from multiple warehouses across the globe, including India depending upon the availability of inventory storage. Customer satisfaction guaranteed. Nº de ref. de la librería NU9780262042192

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Marco Dorigo, Thomas Stutzle
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Descripción MIT Press Ltd, United States, 2004. Hardback. Estado de conservación: New. 230 x 180 mm. Language: English . Brand New Book. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms. Nº de ref. de la librería AAU9780262042192

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10.

Marco Dorigo, Thomas Stutzle
Editorial: MIT Press Ltd, United States (2004)
ISBN 10: 0262042193 ISBN 13: 9780262042192
Nuevos Tapa dura Cantidad: 1
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The Book Depository US
(London, Reino Unido)
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Descripción MIT Press Ltd, United States, 2004. Hardback. Estado de conservación: New. 230 x 180 mm. Language: English . Brand New Book. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms. Nº de ref. de la librería AAU9780262042192

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