Implement a Linear Programming Basically, the program will receive the necessary information for an LP problem namely: The number of variables (that will be equal to the number of constraint coefficients) x The coefficient of each variable for the objective function f(x) The data for the square matrix stating the constraint A The constraint limits b Having all input parameters,we need to compute the possible solution for each variable alone and the solution of the linear equation system Ax = b For example, 3 variables/constraints, [3,2,2] as weights for the objective function, A = [[2,4,5],[1,2,4],[8,0,3]], and b = [300,200,300] Having all input parameters, you will need to compute the possible solution for each variable alone and the solution of the linear equation system Ax = b For this example, the call of linear equation system solution can be: A = np.array([[2,4,5],[1,2,4],[8,0,3]]) inv_A = np.linalg.inv(A) b = np.array([300,200,300] ) x = np.linalg.inv(A).dot(b) The output should be the Real number of unit to each of the variables