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Optimierung unter Unsicherheit mit Hilfe stochastischer Simulation und Genetischer Algorithmen – dargestellt anhand der Optimierung des Produktionsprogramms eines Brandenburger Marktfruchtbetriebes AgEcon
Musshoff, Oliver; Hirschauer, Norbert.
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...
Tipo: Journal Article Palavras-chave: Optimization; Optimal production program; Stochastic simulation; Genetic algorithms; Uncertainty; Stochastic processes; Farm Management; Risk and Uncertainty.
Ano: 2004 URL: http://purl.umn.edu/97454
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