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The manufacture of animal feed is an example of a blending problem. The question is: how do you mix a number of raw components into a minimum cost final blend that has specified amounts of certain ingredients?

In the case of this model, the issure is vital. How can raw feedstocks be combined to produce a high nutrition hogfeed at lowest cost? For someone with several thousand hungry hogs, the quality of this answer can easily spell the difference between profit and loss. Since feedstock prices are typically volatile, the complexity of the question and the daily importance of reliable solutions is even more apparent.

Blending problems are also of interest well beyond the field of animal husbandry. Examples include finding the least costly mix of ores that will produce an alloy with specified characteristics or deciding on the most efficient combination of advertising media purchases to reach target audience percentages in multiple demographic groups.

Objective of Optimization:
The objective is to determine how much of each grain S&R should buy at today's prices to meet their nutritional requirements at lowest cost. This always has a chance of being wrong if price fluctuates unexpectedly.