Balancing economic and environmental goals: A novel strategy for growing items acquisition in livestock farming under an incremental discount and a power demand pattern

Abstract

The human food supply chain is significantly influenced by growing items (GIs) like beef, sheep, hog, chicken, turkey, and other species, as these provide major contributions to food security worldwide. Industrial farming businesses carry out their operations by purchasing a certain species of baby GIs from a supplier, feeding and caring for them until they reach an acceptable living weight, and then selling them after they have been slaughtered and processed. In addition, the production of livestock worldwide accounts for 14.5% of all anthropogenic greenhouse gas (GHG) emissions, according to the Food and Agriculture Organization (FAO), making it a substantial contributor to GHG emissions. Thereby, to regulate emissions, governments from several countries have imposed a tax scheme on the farm’s emission volume. Due to the discrete nature of purchase numbers, using a differentiation-based optimization approach is not appropriate for determining the optimal GI procurement for an industrial farm, making the decision significantly more challenging. The primary goal of this study is to identify the optimal number of GIs for a farm to enhance financial and environmental performance when the cost per weight unit of procurement depends on the volume of purchases and the consumption of processed commodities follows a power demand pattern. A comparison tactic is employed only for the discrete decision variable, while the classical optimization tactic, based on differentiation, is adopted for the remaining continuous decision variable of the derived problem. Our method, which is quite straightforward in its operation, enables the creation of a rule to distinguish between instances in which there is only one optimum solution and those in which there are two. The results from the execution of the novel solution technique reveal that the farm reduces the overall cost of the order while keeping the integrality of the purchased GIs by taking into account the regulation for carbon emissions, the discount, and the power demand pattern.