Evolution Strategy and Social Sciences

  • Hermann Krallmann
Part of the NATO Conference Series book series (NATOCS, volume 5)

Abstract

A model is confronted with respect to its structure and its behavior by minimum requirements which it should meet in order to be acceptable. In most of the cases, these specifications grow out of experience of practical applications. The hitherto existing common procedure consists of modifying defined parameters and structures, dependent on the results of actual system behavior analysis to adapt the system behavior to desired conditions. This method is satisfactory with models of less complexity [1].

Keywords

Evolution Strategy Service Sector System Dynamics Model Multiple Element Demand Situation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    D. Bell and A. W. Griffin, Regelkreistheorie und Datenverarbeitung, Berlin, 1971, S. 241.Google Scholar
  2. 2.
    I. Rechenberg, Evolutionsstrategie Optimierung technischer Systeme nach Prinzipien der biologischen Evolution, Stuttgart, 1973.Google Scholar
  3. 3.
    System Dynamics was developed by Jay W. Forrester at M.I.T. to analyse complex, nonlinear and dynamic systems, Jay W. Forrester, Industrial Dynamics, Cambridge, 1961. The most well known applications of System Dynamics are: D. Meadows et al., Die Grenzen des Wachstums, Bericht des Club of Rome zur Lage der Menschheit, Stuttgart, 1972 and Jay W. Forrester, World Dynamics, Cambridge, Mass., 1971.Google Scholar
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    G. Lehmann, Wirtschaftswachstum im Gleichgewicht. Eine System Dynamics-Studie sozio-ökonomischer Entwicklungen in der Bundesrepublik Deutschland bis zum Jahre 2000, Stuttgart 1975, pp. 114–308.Google Scholar
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    Determinant variables of coefficients of the allocation function of employees are the investment plans of the firms and the time t. The amount of investment of the service sector results from multiplication of the whole national economy investment amount with the variable INVA3.Google Scholar
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    H. Krallmann, Heuristische Optimierung von Simulationsmodellen mit Razor Search Algorithmus, Basel U. Stuttgart 1976.Google Scholar
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    H. Krallmann, “Optimization of Simulation Models in a Feed-backloop-Structure.” In: Proceedings of the 1975 Summer Computer Simulation Conference (SCSC), San Francisco, July 1975.Google Scholar
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    C. W. Nelson, H. M. Krisbergh, “A Search for Policy Oriented Simulations: Applications to Urban Dynamics.” In: Management Science 20(8), April 1974, Serie B, 1164–1172.Google Scholar
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    The following explanations rely heavily on the work of Dr. Hans P. Schwefel to whom I am very much indebted. H. P. Schwefel, Numerische Optimierung von Computer-Modellen mittels der Evolutionsstrategie, Basel und Stuttgart, 1977, pp. 123–149.Google Scholar
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    P. Plaschko and K. Wagner, Evolutions-Linearisierung zur Darstellung von numerischen Daten durch beliebige Funktionen, Berlin 1973,Google Scholar
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    D. Hartmann, Optimierung balkenartiger Zylinderschalen aus Stahlbeton mit elastischem und platischem Werkstoff-verhalten, Diss. Berlin 1974.Google Scholar

Copyright information

© Springer Science+Business Media New York 1978

Authors and Affiliations

  • Hermann Krallmann
    • 1
  1. 1.IndustrieseminarUniversitat MannheimMannheimWest Germany

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