When we consume meat products, we rarely think of the complex problems faced by those engaged in meat production. The meat industry is expected to provide consumers with a wide array of products, while still maintaining profitability. The task of cutting animal carcasses for human consumption and deciding on the amounts of each product to supply to different markets has become a complex linear programming problem. In the meat industry, the objective is to maximize the return on the sale of the end products for which there is the least demand.
The components involved in such a meat industry problem include patterns used to partition the carcasses, cutting time, and demand. Secondary considerations include carcass availability, grade, weight, and cost, as well as distribution, packaging, and exchange rates.
A realistic problem in partitioning lamb carcasses for sale produces 11 grades, two cutting methods, 500 product demands, and about 1000 cutting patterns. Such a problem involves a very large number of both decision variables and constraints. The Meat Industry Research Board of New Zealand has developed an IBM linear programming solver which uses a DOS database and a "C" program to solve these problems and check the solutions. This system is expected to increase marketability of the available end products and thus increase profits.