Linear Programming is a mathematical technique used to solve problems of allocating limited resources among the competing activities.

Linear programming is probabilistic in nature.

For an LPP having " n " decision variables, there must be an equal number of constraints.

Variables can be unrestricted in the context of an LPP.

Graphical method of linear programming is not useful when there are only two decision variables.

Objective function specifies the dependent relationship between the decision variables and the objective function.

Optimum solution to an LPP always lies at least on the two vertices of the feasible region.

It is possible for the objective function value of an LPP to be the same at two distinct extreme points.

Solution of maximization LPP when permitted to be infinitely large is called unbounded.

An LPP is said to have feasible solution if it does not satisfy all the constraints of the problem.

An LPP, with all its constraints are of the type ≥, is said to be in standard form.

An LPP, with all its constraints are of the type ≤, is said to be in canonical form.

Exclusion of a redundant constraint does not affect the optimal solution to an LPP.

Slack variables are used to convert the inequalities of the type ≤ into equations.

In maximization LPP, there is no need to introduce artificial variables.

The co-efficients of slack/surplus variables into objective function are

Surplus variables are used to convert the inequalities of the type ≥ into equations.

In maximization LPP, there is no need to introduce artificial variables.

For solving an LPP by Simplex Method, it is necessary that all unrestricted variables are first replaced by non-negative variables.

In Simplex method, once a variable leaves the basis, it can not reenter the same.

The coefficients of slack/surplus variables are always zero in the objective function.

In Simplex table, if all the elements in the key column are negative, then there is an unbounded solution.

For each of the basic variables in a given solution, whether optimum or not, (z_j - c_j) equals zero.

To decide the departing variable in a simplex table giving a non-optimum solution, the least non-negative replacement ratio is selected.