© 1998

Bio-Mimetic Approaches in Management Science

  • Jacques-Marie Aurifeille
  • Christophe Deissenberg

Part of the Advances in Computational Management Science book series (AICM, volume 1)

Table of contents

  1. Front Matter
    Pages i-x
  2. Patrick Gallinari, Tautvydas Cibas
    Pages 13-25
  3. Hennie Daniels, Bart Kamp, William Verkooijen
    Pages 27-45
  4. Jean-François Casta, Bernard Prat
    Pages 47-59
  5. R. Boné, R. Thillier, F. Yvon, J. P. Asselin de Beauville
    Pages 153-162
  6. Mohamed Slimane, Gilles Venturini, Jean-Pierre Asselin de Beauville, Thierry Brouard
    Pages 179-196

About this book


Management Science is often confronted with optimization problems characterised by weak underlying theoretical models and complex constraints. Among them, one finds data analysis, pattern recognition (classification, multidimensional analysis, discriminant analysis) as well as modelling (forecasting, confirmatory analysis, expert system design). In recent years, biomimetic approaches have received growing attention from Marketing, Finance and Human Resource researchers and executives as effective tools for practically handling such problems. Biomimetic approaches include a variety of heuristic methods - such as neural networks, genetic algorithms, immunitary nets, cellular automata - that simulate nature's way of solving complex problems and, thus, can be considered as numerical transpositions of true life problem solving.
Bio-Mimetic Approaches in Management Science presents a selection of recent papers on biomimetic approaches and their application to Management Science. Most of these papers were presented at the last ACSEG/CAEMS International Congresses (Approches Connexionnistes en Sciences Economiques et de Gestion/Connectionnist Approaches in Economics and Management Science). All papers combine the discussion of conceptual issues with illustrative empirical applications, and contain detailed information on the way heuristics are practically implemented. The advantages and limits of the biomimetic approaches are discussed in several of the papers, either by comparing these approaches with more classical methods (logit models, clustering), or by investigating specific issues like overfitting and robustness. Synthesizing overviews are provided, as well as new tools for coping with some of the limitations of biomimetic methods.


Design Finance Japanese End User List Management Marketing Stress data analysis

Editors and affiliations

  • Jacques-Marie Aurifeille
    • 1
  • Christophe Deissenberg
    • 2
  1. 1.University of PoitiersFrance
  2. 2.University of NantesFrance

Bibliographic information

  • Book Title Bio-Mimetic Approaches in Management Science
  • Editors Jacques-Marie Aurifeille
    Christopher Deissenberg
  • Series Title Advances in Computational Management Science
  • DOI
  • Copyright Information Springer-Verlag US 1998
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Hardcover ISBN 978-0-7923-4993-8
  • Softcover ISBN 978-1-4419-4791-8
  • eBook ISBN 978-1-4757-2821-7
  • Series ISSN 1388-4301
  • Edition Number 1
  • Number of Pages X, 208
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Business and Management, general
    Finance, general
    Human Resource Management
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