Justification of mechanisms of optimization of technological-economic parameters of dairy farms and complexes of different production capacity

The article emphasizes the need for the development of animal husbandry in terms of its degradation, provides actual statistics that illustrate the negative trends in the development of the entire industry in the recent period. The material of the article reveals the main points of the problem, which is related to changes in technological parameters of enterprises of different production capacity. These changes concern, first and foremost, the uneven variation in all types of resource costs in monetary terms, even within enterprise groups with respect to the same output indicators. The complexity of the problem is compounded by the fact that, with various technological re-equipment, cost changes have a complex nature of correlation. Determined drivers of the impact on overall costs were productivity, livestock cows and the amount of variable costs, the main importance of which is the cost of feed. Based on the actual data of the milk producers of Kharkiv region, the method of optimization of technological and economic parameters of enterprises of different production capacity has been developed and the functional dependences of total costs on cow productivity, number of livestock and variable costs are determined and presented. The mechanism of optimization of technological and economic parameters consists in the given equations of multiple nonlinear regression for enterprises with production up to 20 thousand tons of milk per year (small production capacity), from 20 to 60 thousand tons (average) and enterprises of high capacity - from 60 to 100 ths. milk per year, which make it possible to universally evaluate and calculate patterns of interaction of influential factors, to obtain their quantitative characteristics within the graduation of the corresponding capacity of enterprises. The multiple correlation coefficient between influential traits (productivity, livestock numbers, and variable costs) is, respectively, Rm = 0.784404; Rm = 0.966627 and Rm = 0.56011. The average relative error of approximation is 10.1%; 10.5% and 13.9% respectively. The above methodical approach reveals the principles of mechanisms for solving the problems of optimization of technological parameters through multifactorial nonlinear functional dependencies by creating adequate forecasting models with further minimization of variable costs at the required installed capacity.