Agriculture Reference
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their land and corresponding cost and structural data. The linear
optimization approach is a mathematical planning tool based on linear
relations that is frequently used for the determination of crop
competitiveness (Rafsnider
et al.
1993; Rae 1994). Koopmanns defined it
as a method that optimizes total output by simultaneously considering
competing production activities to find the solution that maximizes a
dignified goal, given various restrictions and limitations (Steinhauser
et al.
1992).
The general static linear optimization approach maximizes some
objective function,
G,
considering production activities
corresponding function values
and limited resources
Production was constrained so that the sum of resources used across
production activities did not exceed resource availability, or
A non-negative condition on resource use was also imposed
The optimization models required several assumptions about
producers' objective functions and resource use. Our analysis assumed that
farmers maximize profit. Also it assumed: production activities were linear
(constant factor to product relation), inputs were divisible to any unit size,
activities were additive and independent, all production occurred in the
same period, production capacities were constant, no dis-investment or
saving occurred, farms remained solvent, and production was guaranteed
(Kruschwitz 1995; Brandes and Woerman 1982; Steinhauser
et al.
1992;
Hillier and Liebermann 1998).
The basic farm model used in the analysis was a farm with 40 ha of
arable land with an addition of up to 10 ha rented. Annual farm household
labor availability was 800 hours for crop activities with seasonal
limitations (max 200 hours per season
2
). Additional labor could be hired at
20 DM per hour. Several other constraints—for example, regarding crop
rotation of hemp and other crops
were made. Quotas and processing capacities limited the cultivated area of
sugar beets and potatoes. Animal production was not considered. The
objective of the farmer was to maximize the total net returns.
Data requirements of the analysis included yields, commodity
prices, production costs and subsidy payments for hemp and primary
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