Unconstrained Optimization Packages

TNPACK	Author	Tamar Schlick Courant Institute of Mathematical Sciences 251 Mercer Street New York, NY 10012 Phone: (212) 998-3116 E-mail: schlick@cims.nyu.edu Aaron Fogelson University of Utah,Department of Mathematics, Salt Lake City, Utah, 84112
	Language	Fortran 77
	Algorithm	Truncated Newton Method using the preconditioned conjugate gradient algorithm
	Input Format
	Modeling Languages link
	Commercial Status	free
	Platform	Any machine with a reasonable amount of memory and a Fortran compiler
	Remarks	TNPACK uses a preconditioned conjugate gradient method to solve the Newton equations approximately at every step. Modifications are incorporated to handle indefiniteness of both the Hessian and the preconditioner. The preconditioning matrix (usually a sparse approximation to the Hessian) is provided by the user. It is factored by a sparse modified Cholesky factorization based on the Yale Sparse Matrix Package. TNPACK is intended to solve complex problems that arise in practical applications, such as computational chemistry and biology, where a natural separability or hierarchy in complexity exists among the different functional components. The user can adapt details of the algorithm to suit the problem at hand (for example, by preconditioning and variable reordering).
	References	T. Schlick and A. Fogelson, TNPACK -- A truncated Newton minimization package for large-scale problems. I: Algorithm and usage, ACM. Trans. Math. Software 18 (1992), pp. 46--70. T. Schlick and A. Fogelson, TNPACK -- A truncated Newton minimization package for large-scale problems. II: Implementation examples, ACM. Trans. Math. Software 18 (1992), pp. 71--111. T. Schlick and W. K. Olson, Supercoiled DNA structure and dynamics by computer simulations, J. Mol. Biol. 223 (1992), pp. 1089--1119. T. Schlick and M. L. Overton, A powerful truncated Newton method for potential energy functions, J. Comp. Chem., 8 (1987), pp. 1025--1039.