Use MATLAB or Python

6.11 Write a routine implementing the BFGS method of Section 6.3.5 for unconstrained min imization. For the purpose of this exercise, you may refactor the resulting matrix B at each it- eration, whereas in a real implementation you would update either B-1 or a factorization of B to reduce the amount of work per iteration You may use an initial value of Bo - I, but you might also wish to include an option to compute a finite difference approximation to the Hessian of the objective function to use as the initial Bo. You may wish to include a line search to enhance the robustness of your rou- tine. Test your routine on some of the other computer problems in this chapter, and com pare its robustness and convergence rate with those of Newton's method and the method of steepest descent 6.11 Write a routine implementing the BFGS method of Section 6.3.5 for unconstrained min imization. For the purpose of this exercise, you may refactor the resulting matrix B at each it- eration, whereas in a real implementation you would update either B-1 or a factorization of B to reduce the amount of work per iteration You may use an initial value of Bo - I, but you might also wish to include an option to compute a finite difference approximation to the Hessian of the objective function to use as the initial Bo. You may wish to include a line search to enhance the robustness of your rou- tine. Test your routine on some of the other computer problems in this chapter, and com pare its robustness and convergence rate with those of Newton's method and the method of steepest descent