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Abstract
The modern concept of rural development implies the use of agricultural resources,
primarily agricultural land, for other (non-agricultural) activities besides its agricultural
purpose. The integral aim of this concept of rural development is the maximization of
economic results, besides the sustainable development of rural areas, environmental
protection and the production of strategic (staple) agricultural products.
The objective of this paper is to define the general, theoretical, quantitative model for
the determination of the size and quality of agricultural land which, considering the
above-mentioned demands (criteria) is optimal for the utilization in agricultural
production in certain regions. The remaining agricultural land would be available for
the non-agricultural purposes.
The economic optimal model for the selection of agricultural land in the traditional
agriculture is the model of linear programming. The criteria of the land selection
for traditional agriculture are the economic effectiveness (measured by net income
or by gross national product) and the economic efficiency (measured by the
production economy). The maximum economic effectiveness is determined by the
standard method of linear programming and the maximum economy by the method
of broken linear programming. The solution of compromise can be determined by
multi-criteria programming, based on the minimum differences.
The limitation groups in the mentioned variations of the model are: limitations of
production quotas of agricultural products, minimum quantities of staple agricultural
products, limitations of processing plants in a region (minimum and maximum),
limitation of crop rotation, limitations of the needs in animal husbandry for bulky forage
and limitations of agricultural land according to various types of utilization. By
quantitative defining of the structure and size of agricultural land for traditional
agriculture, “the surplus” and structure of agricultural land available for non-agricultural
purposes is automatically determined.