mathematical approach to the problem of allocating limited resources among competing activities in an optimal manner. Specifically, it is a technique used to maximize revenue, Contribution Margin (CM), or profit function or to minimize a cost function, subject to constraints. Linear programming consists of two important ingredients: (1) objective function and (2) constraints, both of which are linear. In formulating the LP problem, the first step is to define the decision variables that one is trying to solve. The next step is to formulate the objective function and constraints in terms of these decision variables. For example, assume a firm produces two products, A and B. Both products require time in two processing departments, assembly and finishing. Data on the two products are as follows:
a mathematical model for decisions with a large number of alternatives. LP is typically used to either maximize profit or minimize costs in a manufacturing process with varying levels of inputs.
