Farm management optimization using chance constrained programming method

This paper presents a stochastic optimization model to determine the optimal number of acres of hay a farm should harvest for their own horses’ consumption, as well as how much hay to purchase and sell to maximize the total profit of the farm. This research is motivated by horse farmers who must make yearly decisions concerning the management of feeding horses. These decisions are affected by the cost to grow their own hay, the cost to buy hay, the cost associated with selling hay, and the stochastic nature of crop yield due to different weather conditions. The uncertainty of weather conditions is included in the mathematical model by including random variables in the model constraints. Optimal policies are obtained for a real world case study provided by a Kentucky horse farmer by applying chance constrained programming method. A sensitivity analysis is performed to show the effectiveness of the approach.

► We present a stochastic optimization model to maximize total profit in a horse farm.
► The decisions are affected by various costs and crop yield due to weather conditions.
► The uncertainty of weather conditions is included by random variables in the model.
► Optimal policies are obtained for a real case study using chance constrained method.
► A sensitivity analysis is performed to show the effectiveness of the approach.