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

Area of Science:

• Dairy Science
• Operations Research
• Agricultural Economics

Background:

• Maximizing net revenue in cheese manufacturing requires strategic resource allocation.
• Fluctuations in milk prices and composition present challenges to optimal production planning.

Purpose of the Study:

• To develop and demonstrate a nonlinear programming optimization model for maximizing cheese manufacturing net revenue.
• To analyze the impact of varying milk prices, composition, and nonfat dry milk (NDM) characteristics on optimal production strategies.

Main Methods:

• Developed a nonlinear programming optimization model integrated with Excel and Access for user-friendly data input.
• Simulated scenarios using historical data (1998-2000) to assess the impact of milk price and composition variations.
• Evaluated the profitability of different co-products and the effect of NDM reconstitution methods.

Main Results:

• Optimal resource mix and net revenue significantly varied with changes in milk prices and composition.
• Mozzarella production yielded higher net revenue than Cheddar during periods of high cream prices.
• Whey powder was generally more profitable than whey protein concentrate and lactose; high-protein NDM increased net revenue.

Conclusions:

• Cheese plants must dynamically optimize resource utilization in response to market price and composition shifts to avoid profit loss.
• Strategic use of co-products and high-protein nonfat dry milk (NDM) significantly enhances net revenue.
• Reconstituting NDM with water, rather than milk, can markedly increase net revenue when the value of the nonfat portion of raw milk is high.