Date on Master's Thesis/Doctoral Dissertation


Document Type

Master's Thesis

Degree Name

M. Eng.


Industrial Engineering

Committee Chair

Depuy, Gail W.


Horse farms--Kentucky--Management; Farm management--Data processing


Horse farmers make yearly decisions concerning the management of feeding horses. These decisions are affected by the cost to grow hay, the cost to buy hay, the cost associated with selling hay, the expected crop yield under various weather conditions, and the likelihood of different weather conditions. Most farmers produce their own hay ranging from hundreds to thousands of bales of hay, but also buy hay from other farmers because they either need a different cutting of hay or they need more hay than they can produce. The current method of buying and selling hay is based on the expected value of random factors. A lot of decisions are based on tradition within a farm or how things were done the year before. Because of the way horse farms are currently run, farmers encounter many problems when approaching a new hay season. First, there is often too much hay left over from the previous season. This hay is sold at a reduced price right before a new hay season because the storage area needs to be cleared in preparation for the new and better hay. Hay that has been sitting for an entire winter loses a lot of its nutrients. After a poor hay season, some farmers do not keep enough hay to feed their horses until the next season. They are hopeful for better hay early in the next year and this typically leads to having to purchase higher priced hay before the new hay season. Therefore, it can be seen that, mathematically, taking the expectation as the realization will lead to practically poor solutions. The paper presents a linear programming model to address the current issues with farm management feeding programs. The model will determine how many acres of hay a farm should harvest for their own horses' consumption, as well as how much hay to purchase and sell each period of the season. Solutions are generated for real world parameters provided by a Kentucky horse farmer and a sensitivity analysis is performed. Using the parameters provided, the model concluded that the case study farm is operating with a cost, as opposed to a desired profit, on a yearly basis. The selling price of hay does not help the farm to overcome yearly costs of producing hay. Also, the model shows that the current method of planting all available farming acres is not optimal. This is causing the farm increased cost due to excess inventory. Planting fewer acres means holding inventory for multiple periods to meet demand late in the year. All hay that is not used to meet demand is sold to other farms.