Planning algorithm for efficient and sustainable crop production

Abstract

The process of agricultural production is associated with a complex of factors of a different nature: systemic, technological, biological, socio-economic, climatic, reproductive, environmental. All of them influence the size and stability of economic and financial results. There is a threshold level of enterprise management complexity, the excess of which motivates agribusiness to switch to computerized methods. Management of an agricultural enterprise should be based on planning results, updated in a rolling mode. When developing the annual plan, it is necessary to take into account a lot of heterogeneous information and tend to the optimal solution – the achievement of the target indicators with the minimum expenditure of resources. As the basis of the optimal annual planning system, the article proposes an economic-mathematical model for optimizing the production and industry structure of an agricultural enterprise, which includes the following modules: assessment of the parameters of the yield production functions based on field history, the formation of a fertilizer application plan with justification of economically feasible yield levels, solving the problem of optimizing the sectoral structure of crop production, taking into account the forecrop influence in the crop rotation. The algorithm for finding an effective and stable production structure under various combinations of environmental conditions implements the following sequence of procedures: generation of parameter combinations of the economic-mathematical model; obtaining the optimal solution for each combination of these parameters; assessment of the mathematical expectation of the efficiency criterion and variance for each optimal solution on a variety of parameter combinations; choice of a highly effective solution with a low dispersion of this efficiency. To implement this algorithm, the method of simulation experiments in the space of system parameters is used. The optimal solution is chosen by minimizing the distance to the “ideal point” (maximum efficiency, minimum dispersion).