Evolutionary Algorithms in Management Applications

Jörg Biethahn and Volker Nissen:

ISBN 10: 3540603824 / ISBN 13: 9783540603825

Edité par Springer 01.11.1995., 1995

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379 Seiten nice book ex Library Sprache: Englisch Gewicht in Gramm: 969 24,8 x 17,1 x 2,5 cm, Gebundene Ausgabe.

N° de réf. du vendeur 343816

Détails bibliographiques

• Titre: Evolutionary Algorithms in Management Applications
• Éditeur: Springer 01.11.1995.
• Date de parution: 1995
• Langue: anglais
• ISBN à 10 chiffres: 3540603824
• ISBN à 13 chiffres: 9783540603825
• Reliure: Couverture rigide
• État de l'article: Sehr gut
• Catalogues du vendeur:
  • Alle Bücher

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Synopsis

Evolutionary Algorithms (EA) are powerful search and optimisation techniques inspired by the mechanisms of natural evolution. They imitate, on an abstract level, biological principles such as a population based approach, the inheritance of information, the variation of information via crossover/mutation, and the selection of individuals based on fitness. The most well-known class of EA are Genetic Algorithms (GA), which have received much attention not only in the scientific community lately. Other variants of EA, in particular Genetic Programming, Evolution Strategies, and Evolutionary Programming are less popular, though very powerful too. Traditionally, most practical applications of EA have appeared in the technical sector. Management problems, for a long time, have been a rather neglected field of EA-research. This is surprising, since the great potential of evolutionary approaches for the business and economics domain was recognised in pioneering publications quite a while ago. John Holland, for instance, in his seminal book Adaptation in Natural and Artificial Systems (The University of Michigan Press, 1975) identified economics as one of the prime targets for a theory of adaptation, as formalised in his reproductive plans (later called Genetic Algorithms).

Présentation de l'éditeur

This book is concerned with the application of Evolutionary Algorithms (Ea) in the domain of management. Ea are powerful and broadly applicable search and optimisation techniques based on principles from evolution theory, with Genetic Algorithms being the most well-known class. The first part of this volume introduces to Ea, and contains a discussion of the current state regarding management applications with many useful references. The other parts present papers on innovative management applications of Ea. They range from examples in industry, financial services, trade, and traffic management to planning in education, demonstrating the versatility and power of Ea. The reader will gain an understanding of the field, be able to appreciate the application potential of Ea, and discover many stimulations for own work.