Genetic Algorithms in Engineering and Computer Science: 1st (Wiley series in computational methods in applied sciences)

Gerhard Winter

ISBN 10: 047195859X / ISBN 13: 9780471958598

Editore: Wiley-Blackwell, 1995

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This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:9780471958598.

Codice articolo 7756411

Dati bibliografici

• Titolo: Genetic Algorithms in Engineering and Computer Science: 1st (Wiley series in computational methods in applied sciences)
• Editore: Wiley-Blackwell
• Data di pubblicazione: 1995
• Lingua: Inglese
• ISBN 10: 047195859X
• ISBN 13: 9780471958598
• Rilegatura: Rilegato
• Condizione: Good
• Cataloghi dei venditori:
  • Computing

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Riassunto

Genetic Algorithms in Engineering and Computer Science Edited by G. Winter University of Las Palmas, Canary Islands, Spain J. Périaux Dassault Aviation, Saint Cloud, France M. Galán P. Cuesta University of Las Palmas, Canary Islands, Spain This attractive book alerts us to the existence of evolution based software ? Genetic Algorithms and Evolution Strategies?used for the study of complex systems and difficult optimization problems unresolved until now. Evolution algorithms are artificial intelligence techniques which mimic nature according to the "survival of the fittest" (Darwin?s principle). They randomly encode physical (quantitative or qualitative) variables via digital DNA inside computers and are known for their robustness to better explore large search spaces and find near-global optima than traditional optimization methods. The objectives of this volume are two-fold:

• to present a compendium of state-of-the-art lectures delivered by recognized experts in the field on theoretical, numerical and applied aspects of Genetic Algorithms for the computational treatment of continuous, discrete and combinatorial optimization problems.
• to provide a bridge between Artificial Intelligence and Scientific Computing in order to increase the performance of evolution programs for solving real life problems.

Fluid dynamics, structure mechanics, electromagnetics, automation control, resource optimization, image processing and economics are the featured multi-disciplinary areas among others in Engineering and Applied Sciences where evolution works impressively well. This volume is aimed at graduate students, applied mathematicians, computer scientists, researchers and engineers who face challenging design optimization problems in Industry. They will enjoy implementing new programs using these evolution techniques which have been experimented with by Nature for 3.5 billion years.