An algorithm that minimizes homogeneous functions of N variables in N + 2 iterations and rapidly minimizes general functions

AbstractA new algorithm for function minimization is presented. The new algorithm is based upon homogeneous functions rather than quadratic models. A consequence of this is that (n + 2) step convergence is obtained for homogeneous functions and that no one-dimensional search is required. Preliminary numerical tests indicate that on general functions the algorithm is superior to the well-known Fletcher and Powell method