A FAST conic method for function minimization

A new algorithm for unconstrained minimization is presented, which is based on a conic model. The algorithm converges in (n + 1) iterations on conic functions of n variables and it does not require evaluation or estimation of tbe Hessian matrix. Numerical results on many general test functions indicate tbat the algorithm is very robust and very efficient.