Using Linear Programming To Solve Problems
In real-life situations, linear programming may have to be extended to include additional constraints as they come up.
LP is applied for determining the optimal allocation of such resources as materials, machines, manpower, etc. It is used to determine the optimal product- mix of the firm to maximize its revenue.
It is also used for product smoothing and assembly line balancing.
LP technique enables the personnel manager to solve problems relating to recruitment, selection, training, and deployment of manpower to different departments of the firm.
The business could use the linear programming technique to solve this sort of problem.
The linear programming approach is based on an assumption that the world is linear. There are certain ways of mixing the inputs that a linear programming approach doesn't permit.
It also helps the sales executive of a firm in finding the shortest route for his tour.
Linear Programming, also sometimes called linear optimisation, involves maximising or minimising a linear objective function, subject to a set of linear inequality or equality constraints.
It has great applications in the field of operations management but can be used to solve a range of problems.
Leonard Kantrovich was awarded the 1975 Nobel Price in Economics for the optimal allocation of resources using linear programming.
Examples of problems that can be solved by linear programming include: In this series of posts, we explore some linear programming examples, starting with some very basic Mathematical theory behind the technique and moving on to some real world examples.