Advertisement

Evolutionary Algorithms in Management Applications

  • Jörg Biethahn
  • Volker Nissen

Table of contents

  1. Front Matter
    Pages I-XV
  2. Foundations

    1. Front Matter
      Pages 1-1
    2. Volker Nissen, Jörg Biethahn
      Pages 3-43
  3. Applications in Industry

  4. Applications in Trade

    1. Front Matter
      Pages 197-197
    2. Robert E. Marks, David F. Midgley, Lee G. Cooper
      Pages 225-239
    3. Volker Nissen, Jörg Biethahn
      Pages 240-249
  5. Applications in Financial Services

    1. Front Matter
      Pages 251-251
    2. Neil S. Ireson, Terence C. Fogarty
      Pages 264-276
    3. Steven A. Vere
      Pages 277-289
    4. Michael de la Maza, Deniz Yuret
      Pages 290-302
  6. Applications in Traffic Management

    1. Front Matter
      Pages 303-303
    2. John R. McDonnell, David B. Fogel, Craig R. Rindt, Wilfred W. Recker, Lawrence J. Fogel
      Pages 305-327
    3. Flavio Baita, Francesco Mason, Carlo Poloni, Walter Ukovich
      Pages 341-353
  7. Planning in Education

    1. Front Matter
      Pages 355-355
    2. Werner Junginger
      Pages 357-368
  8. Back Matter
    Pages 369-379

About this book

Introduction

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).

Keywords

Evolutionary Algorithms Genetic Algorithms Genetische Alogrithmen Management Planning algorithms decision support learning local optimization operations research optimization production programming routing scheduling

Editors and affiliations

  • Jörg Biethahn
    • 1
  • Volker Nissen
    • 1
  1. 1.Institut für Wirtschaftsinformatik Abteilung Wirtschaftsinformatik IGeorg-August-UniversitätGottingenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-61217-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 1995
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-64749-9
  • Online ISBN 978-3-642-61217-6
  • Buy this book on publisher's site