TENMIN (See TOMS765 or STENMIN)
Unconstrained optimizer of a nonlinear function of n variables (n <= 100).
Chow, Tu-Tang, Eskow, Elizabeth, and Schnabel, Robert B. (1990). A software package for unconstrained optimization using tensor methods, Technical Report CU-CS-492-90, Department of Computer Science, University of Colorado, December 1990.
Schnabel, Robert B. and Chow Tu-Tang (1991). Tensor methods for unconstrained optimization using second derivatives, SIAM Journal of Optimization, 1, 293_315.
ABSTRACT OR SUMMARY
TENMIN package is intended for solving unconstrained optimization problems where the number of variables n is not too large (n<100, say). The package allows the user to choose between a tensor method for unconstrained optimization and a standard method based on a quadratic model. The tensor method bases each iteration upon a specially constructed fourth-order model of the objective function that is not significantly more expensive to form, store, or solve than the standard quadratic model. Both methods calculate the Hessian matrix and gradient vector, either analytically or by finite differences, at each iteration. The step selection strategy is a line search. The tensor method requires significantly fewer iterations and function evaluations to solve most unconstrained optimization problems than the standard method, and also solves a somewhat wider range of problems. It is especially useful for problems in which the Hessian matrix at the solution is singular. [http://www.ici.ro/camo/unconstr/tenmin.htm]
ORIGINAL CODE LOCATION