Optimierung unter Unsicherheit mit Hilfe stochastischer Simulation und Genetischer Algorithmen - dargestellt anhand der Optimierung des Produktionsprogramms eines Brandenburger Marktfruchtbetriebes -

Abstract: Optimization has been recognized as a powerful tool in teaching and research for a long time. In spite of its well known problem solving capacity, some methodological obstacles have persisted over the years. The main problem is that stochastic variables and their correlations cannot be adequately accounted for within traditional optimization procedures. In this paper, we develop a methodological mix of stochastic simulation and a heuristic optimization procedure which has become known as genetic algorithms. The simulation-part of the mix allows for the consideration of complex information such as stochastic processes; the genetic algorithms-part ensures that the method remains manageable in terms of required time and resources. We demonstrate the decision support potential of the approach by optimizing the production program of a Brandenburg crop farm. We account for the risky environment by using existing stochastic information: on the one hand, we model man-days which are availab.... https://www.tib-op.org/ojs/index.php/gjae/article/view/1601

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Optimierung unter Unsicherheit mit Hilfe stochastischer Simulation und Genetischer Algorithmen - dargestellt anhand der Optimierung des Produktionsprogramms eines Brandenburger Marktfruchtbetriebes - ; volume:53 ; number:7 ; year:2004
Agrarwirtschaft ; 53, Heft 7 (2004)

Creator
Mußhoff, Oliver
Hirschauer, Norbert

DOI
10.52825/gjae.v53i7.1601
URN
urn:nbn:de:101:1-2409251101556.846449113873
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:31 AM CEST

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