Request Inspection Copy

If you are an Academic or Teacher and wish to consider this book as a prescribed textbook for your course, you may be eligible for a complimentary inspection copy. Please complete this form, including information about your position, campus and course, before adding to cart.

* Required Fields

To complete your Inspection Copy Request you will need to click the Checkout button in the right margin and complete the checkout formalities. You can include Inspection Copies and purchased items in the same shopping cart, see our Inspection Copy terms for further information.

Any Questions? Please email our text Support Team on text@footprint.com.au

Submit

Email this to a friend

* ALL required Fields

Order Inspection Copy

An inspection copy has been added to your shopping cart

Ant Colony Optimization

by Marco Dorigo and Thomas Stutzle The MIT Press
Pub Date:
07/2004
ISBN:
9780262042192
Format:
Hbk 319 pages
Price:
AU$99.00 NZ$103.48
Product Status: Available in Approx 14 days
add to your cart
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.
'Inspired by the remarkable ability of social insects to solve problems, Dorigo and Sttzle 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 The MIT Press
Marco Dorigo is research director of the IRIDIA lab at the Universit+® Libre de Bruxelles and the inventor of the Ant Colony Optimization metaheuristic for combinatorial optimization problems. Thomas Stützle is Assistant Professor in the Computer Science Department at Darmstadt University of Technology.