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Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks

Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks

Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated
Stock photo: cover may vary

Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks Hardback - 2000

by Pham, Duc

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  • Hardback

Description

Springer-Verlag, 2000. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In poor condition, suitable as a reading copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9781852330286
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Details

  • Title Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks
  • Author Pham, Duc
  • Binding Hardback
  • Edition U. S. EDITION
  • Pages 302
  • Volumes 1
  • Language ENG
  • Publisher Springer-Verlag, Secaucus, New Jersey, U.S.A.
  • Publication date 2000
  • Illustrated Yes
  • Bookseller's Inventory # 8237211
  • ISBN 9781852330286 / 1852330287
  • Weight 1.34 lbs (0.61 kg)
  • Dimensions 9.39 x 6.34 x 0.94 in (23.85 x 16.10 x 2.39 cm)
  • Category Technology & Industrial Arts
  • Library of Congress Catalogue Number 98-15571
  • Dewey Decimal Code 620.002

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Reader reviews for Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks

From the publisher

This book covers four optimisation techniques loosely classified as "intelligent": genetic algorithms, tabu search, simulated annealing and neural networks. Genetic algorithms (GAs) locate optima using processes similar to those in natural selection and genetics. Tabu search is a heuristic procedure that employs dynamically generated constraints or tabus to guide the search for optimum solutions. Simulated annealing finds optima in a way analogous to the reaching of minimum energy configurations in metal annealing. Neural networks are computational models of the brain. Certain types of neural networks can be used for optimisation by exploiting their inherent ability to evolve in the direction of the negative gradient of an energy function and to reach a stable minimum of that function. Aimed at engineers, the book gives a concise introduction to the four techniques and presents a range of applications drawn from electrical, electronic, manufacturing, mechanical and systems engineering. The book contains listings of C programs implementing the main techniques described to assist readers wishing to experiment with them. The book does not assume a previous background in intelligent optl1TIlsation techniques. For readers unfamiliar with those techniques, Chapter 1 outlines the key concepts underpinning them. To provide a common framework for comparing the different techniques, the chapter describes their performances on simple benchmark numerical and combinatorial problems. More complex engineering applications are covered in the remaining four chapters of the book."
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