An algorithm is proposed for minimizing certain nice C2 functions f on En assuming only a computational knowledge of f and grad f. It is shown that the algorithm provides global convergence at a rate which is eventually superlinear and possibly quadratic. The algorithm is purely algebraic and does not require the minimization of any functions of one variable. Numerical computation on specific problems with as many as six independent variables has shown that the method compares very favorably with the best of the other known methods. The method is compared with the Fletcher and Powell method for a simple two dimensional test problem and for a six dimensional problem arising in control theory. (Author).
"An algorithm is proposed for minimizing certain nice C2 functions f on En assuming only a computational knowledge of f and grad f. It is shown that the algorithm provides global convergence at a rate which is eventually superlinear and possibly quadratic. The algorithm is purely algebraic and does not require the minimization of any functions of one variable. Numerical computation on specific problems with as many as six independent variables has shown that the method compares very favorably with the best of the other known methods. The method is compared with the Fletcher and Powell method for a simple two dimensional test problem and for a six dimensional problem arising in control theory. (Author)."@en
BOEING SCIENTIFIC RESEARCH LABS SEATTLE WASH MATHEMATICS RESEARCH LAB.
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