A many-objective optimization approach for weight gain and animal welfare in rotational grazing of cattle

The "multidimensional"nature of the concept of welfare is reflected in the definition proposed by the World Organization for Animal Health (OIE), according to which an animal is in a satisfactory state of welfare when it is healthy, comfortable, and well-fed, can express its innate behavior, and does not suffer pain, fear, or distress. Many of these aspects, in the real context of a cattle farm, are not considered, and most of the farmers' decisions are based on their experiences. In this proposal, we establish a many -objective optimization model for rotational grazing allocation based on six objectives that consider cattle weight gain and travel, as well as their welfare. The model is solved using the NSGA-III algorithm, and its performance is evaluated using a simulation study of 90 days of rotational grazing in which it is compared with the traditional grazing strategy. Average weight gains of up to 36.7 kg per animal are achieved at the end of the three months of simulated grazing using the proposed model. The results indicate that the allocation model generates an average weight gain that is statistically greater than that generated by the traditional rotation method but also guarantees improved animal welfare, the main contribution of our approach.