The managing director of a steel plant faces the decision to order how much of each raw material for the plant for the following month. Because of lower and upper bounds for the quantities of each commodity in a batch, and different amounts of electricity consumed and time for various raw materials, you simply can not be the cheapest commodity. A linear optimization program, and the solver function of Excel provides the optimal amounts which satisfy the constraints. Interestingly, the best mix … Read more »

The managing director of a steel plant faces the decision to order how much of each raw material for the plant for the following month. Because of lower and upper bounds for the quantities of each commodity in a batch, and different amounts of electricity consumed and time for various raw materials, you simply can not be the cheapest commodity. A linear optimization program, and the solver function of Excel provides the optimal amounts which satisfy the constraints. Interestingly, the best mix for a batch not the best mix for a monthly plan. Shadow prices show the value of relaxing restrictions. A typical model of a monthly students are not linear, though it can be described as a linear model. This case provides the basis for an introductory class on linear programming and linear to nonlinear models.
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from
Samuel E physical,
Akshay Mittal
Source: Darden School of Business
4 pages.
Release Date: 6 April 2011. Prod #: UV6307-PDF-ENG
Chandpur Enterprises Limited, Steel Division HBR case solution