Solving Linear Programming using Python PuLP
Learn how to use Python PuLP to solve linear programming problems.
As a Senior operation manager, your job is to optimize scarce resources, improve productivity, reduce cost, and maximize profit. For example, you want to maximize the profit of the manufacturing unit with constraints like labor working hours, machine capacity, and available raw material. Another example is that a marketing manager wants to allocate the optimum budget among alternative advertising media channels such as radio, television, newspapers, and magazines. Such problems can be considered optimization problems.
Optimization problems can be represented as a mathematical function that captures the tradeoff between the decisions that need to be made. The feasible solutions to such problems depend upon constraints specified in mathematical form.
Linear programming is the core of any optimization problem. It is used to solve a wide variety of planning and supply chain optimization. Linear programming was introduced by George Dantzig in 1947. It uses linear algebra to determine the optimal allocation of scarce resources.
