solve the LP problem with Bland's rule to resolve degeneracy. Also the output from linprog, does it mean there is no solution? Please show with steps. Thank you.

Solve the following linear program using Bland's rule to resolve degeneracy: maximize 10x1 57x2 - 9x3 - 24x4 subject to 0.5x1 - 5.5x2 - 2.5x3 + 9x40 0.5x11.5x2 0.5x3+ x40 X1 Note Does lhs_ineq rhs_ineq bnd = the following output from linprog this is solution? = from scipy.optimize import linprog obj= [-10, 57, 9, 24] mean print (opt) 1 X1, X2, X3, X4 0. [0,0,1] there [[0.5,-5.5,-2.5,9],[0.5,-1.5,-0.5,1],[1,0,0,0]] [(0, float("inf"))]*4 opt = linprog (c=obj, A_ub=lhs_ineq, b_ub=rhs_ineq, bounds bnd, method="revised simplex") success: False con: array([], dtype=float64) fun: 0.0 message: 'Iteration limit reached. nit: 5000 slack: array ( [0., 0., 1.]) status: 1 no x: array ( [0., 0., 0., 0.1)