Powell’s gradient-free methods[20] provide directions
of search that line up with directions conjugate
about the Hessian matrix of the quadratic approximation
to the objective function. The Powell method applied in
the current study is the version described in[21, 1], in
which an initial guess and a set of independent search directions
are provided to the algorithm. In each iteration
the method serially performs a sequence of line minimizationsrections remain linearly independent. The iteration is
terminated when either the convergence rate or the error
between the predicted and the exactsolutions are smaller
than prescribed values. The Powell’s method described
above will converge to the minimum of a quadratic function
in a finite number of iterations[4].
along the various directions in the space of
parameters. At the end of each iteration the method replaces
one of the original directions with the line joining
the starting and ending points. The Figure 3 illustrates
the Powell method. Care is taken to ensure that the di