A nonlinear programming optimization model to maximize net revenue in cheese manufacture.

A nonlinear programming optimization model was developed to maximize net revenue in cheese manufacture and is described in this paper. The model identifies the optimal mix of milk resources together with the types of cheeses and co-products that maximize net revenue. It works in Excel while it takes the data specified by the user from a user-friendly interface created in Access. The user can specify any number of resources, cheese types, and co-products. To demonstrate the capabilities of the model, we determined the impact of variation in milk price and composition in the period 1998 to 2000 on the optimal mix of resources and optimal type of co-product for Cheddar and low-moisture, part-skim Mozzarella. It was also desired to determine the impact of variation in protein content of nonfat dry milk (NDM) on net revenue, and examine the effect of reconstitution of NDM with water versus milk on net revenue. The optimal mix of resources and the net revenue markedly varied as milk resource prices and composition varied. The net revenue for Mozzarella was much higher than for Cheddar when the price of cream was high. Cheese plants that did not optimize the use of resources in response to variations in prices and composition missed a significant profit opportunity. Whey powder was more profitable than 34% whey protein concentrate and lactose in most months. The use of high-protein NDM led to an appreciable increase in net revenue. When the value of the nonfat portion of raw milk was high, reconstitution of NDM with water rather than milk markedly raised net revenue.