The standard form of a Linear Programming (LP) problem involves maximizing or minimizing a linear objective function \( c^T x \) subject to a set of equality constraints \( Ax = b \) and non-negativity constraints \( x \geq 0 \). Here, \( c \) is a vector of coefficients for the objective function, \( A \) is a matrix of coefficients for the constraints, \( b \) is a vector of constants, and \( x \) is a vector of decision variables, all of which must be non-negative. This structure facilitates the use of various solution methods in linear programming.