Linear Programming: Blending

Topics: Elementary algebra, Operations research, Decision making Pages: 2 (609 words) Published: August 8, 2008
Linear programming is a technique which shows practical problems as a series of mathematical equations which can be manipulated to find the optimum or best solution. Blending is a graphical approach to linear programming which deals with resource allocation subject to constraints. It is a model which assists firms in deciding the best possible utilisation of limited resources. Each resource constraint is represented as a mathematical linear equation. A linear expression is an equation which links two variables, and if plotted on a graph, would be represented by a straight line. By plotting all the equations, the optimal use of the business's resources can be easily identified.

Blending can be useful to firms when deciding how to make the best use of their resources. Businesses can use this method to allocate factors of production so that profits are maximised or costs minimised, depending on the business's objective. Another advantage of blending is that is allows the business to decide a combination of the two goods to produce, as compared to other invest appraisal or decision making techniques where either one or the other option must be selected, but not both.

Blending is a fairly easy and fast technique as it only requires simple calculations. The results are also represented on a graph and so information can be seen visually and do not require much explanation. Additionally, computers can speed up the calculations and increase the methods accuracy.

However, blending has its limitations. It does not take into account the market demand for the products. The assumption is that the optimum output level for each good will be sold profitably, which may not be the case. Producing at the most profitable output level will not matter if the products cannot be sold.

This technique also assumes that resources can be switched between the two products at a constant rate of productivity. This may not be a realistic assumption. For example, the machines in a...
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