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In Hungary hundreds of thousands of cows produce milk for us. A common disease of them is mastitis that influences their productivity and profitability substantially. The usual practice is to decide on a rule of thumb basis whether the ill cow should be kept or sold. E.g. they are kept till the fifth mastitis case occurs. The present study investigates this problem from a mathematical modelling point of view. The relative amount of the possible lost profit is in the order of magnitude of 10s of percentages, which is quite large, especially regarding the profitability outlooks of the dairy branch.
The problem lies in the personal relationship of the farmers to the cows, and in the complexity of the estimation of the uncertain future scenarios. We present a model that is based on collected historical data on the distribution of several model parameters such as the length of the illness, the amount of medicine needed, the number of inseminations required to get into the next lactation cycle etc. The applied methodology is microsimulation (i.e. we simulate all possible events one-by-one) and stochastic optimization. Our typical result is a suggested decision on the basis of the expected value of the profit/loss for the given animal.
We report on the first results that confirm our research expectations in terms of improvement of the business decision. The ongoing research will focus on a recommendation system type data mining technology that can utilize the local specialties of the actual dairy farm in question, and to validate the additional advantage involved in it.