Linear programming

Here I come with another complex topic in math. I know that sounds boring but let us try to make it simpler so that we can understand the same.

Linear programming, sometimes known as linear optimization, is the problem of maximizing or minimizing a linear function over a convex polyhedron specified by linear and non-negativity constraints. Simplistically, linear programming is the optimization of an outcome based on some set of constraints using a linear mathematical model. Linear programming in which variables may take on integer values only is known as integer programming.

The Linear Programming plan helps to maximize the profit or else minimize the cost subject to the limitations. The profit or the cost is made up of unknown quantities. These unknowns are variables of the degree; one and they are called decision variables. The profit or else the cost are a linear function of these variables. These in equations are called constraints. The linear programming simplex (LPX) is to maximize or minimize the aim function subjected to the Linear Programming constraints.

This does not end here. Lot more to come so keep in touch…. Thank you for reading this post.