A multi-objective optimization model to maximize cattle weight-gain in rotational grazing

Rotational grazing can improve cattle feeding considering a series of aspects, such as (1) the maximum utilization of each hectare of pasture on which the cattle are fed and; (2) the pasture analysis to guarantee the type and the size of the pasture that will serve as feed, among others. The above aspects allow better-fed cattle, with better weight and meat quality. To implement rotational grazing, it is necessary to carry out forage-utilization practices with criteria associated with the morphophysiology and phenology of the forage species. Many of these data, in the real context of a beef farm, are not used, and most of the decisions made by the farmer are based on experience (successes and failures in productivity). In this proposal, we establish a multi-objective rotational-grazing assignment model based on (1) the best quality forage, and (2) the distance an animal must travel from one paddock to another. At each stage, we estimate the amount of forage as well as the total weight of each batch of animals. Based on pasture yield and cattle forage demand, we propose a dynamic assignment model. To validate the effectiveness of the assignment model, we carried out a discrete simulation of a one-year cattle rotation. Results show that the assignment model generates a statistically higher average weight gain than the one generated by the traditional rotation method.