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

Oliver Musshoff and Norbert Hirschauer

German Journal of Agricultural Economics, 2004, vol. 53, issue 07, 16

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 available in critical seasons (particularly harvesting) as triangular distributions according to expert estimations. On the other hand, we use empirical time series and estimate stochastic processes for the gross margins of different activities (wheat, barley etc.). Additionally, variant calculations are made in order to take into account different risk attitudes of decision-makers. Model results in terms of optimal production programs and expected total gross margins are highly sensitive both to the risk attitudes of decision-makers and the stochastic processes which are estimated for different activities.

Keywords: Farm Management; Risk and Uncertainty (search for similar items in EconPapers)
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://ageconsearch.umn.edu/record/97454/files/2_Musshoff.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:gjagec:97454

DOI: 10.22004/ag.econ.97454

Access Statistics for this article

More articles in German Journal of Agricultural Economics from Humboldt-Universitaet zu Berlin, Department for Agricultural Economics Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().