toms611

toms611, a FORTRAN90 code which carries out the unconstrained minimization of a scalar function, by David Gay.

The code is a FORTRAN90 implementation of ACM TOMS algorithm 611.

The code contains routines for the general unconstrained minimization of a scalar function of several variables. The routines use a model/trust-region approach, and the double-dogleg technique of Dennis and Mei. In cases where the Hessian is not supplied by the user, the BFGS secant update is used instead.

Three different implementations of the algorithm are available, which allow the user to supply just the function, the function and gradient, or function, gradient and hessian.

The user may also choose to supply the information about the function through subroutines, or to use a version of the algorithm that employs "reverse communication", allowing the user to evaluate the function in any suitable way.

The text of many ACM TOMS algorithms is available online through ACM: https://calgo.acm.org/ or NETLIB: https://www.netlib.org/toms/index.html.

Licensing:

The computer code and data files made available on this web page are distributed under the MIT license

Languages:

toms611 is available in a FORTRAN90 version.

Related Data and Programs:

BRENT, a FORTRAN90 code which contains routines for finding zeroes or minima of a scalar function of a scalar variable, without the use of derivative information, by Richard Brent.

BVLS, a FORTRAN90 code which applies least squares methods to solve a linear system for which lower and upper constraints may have been placed on every variable.

COMPASS_SEARCH, a FORTRAN90 code which seeks the minimizer of a scalar function of several variables using compass search, a direct search algorithm that does not use derivatives.

test_lls, a FORTRAN90 code which implements linear least squares (LLS) test problems which are given A and b, and seek a vector x which minimizes the L2 norm of the error ||Ax-b||.

TEST_OPT, a FORTRAN90 code which defines test problems for the minimization of a scalar function of several variables.

TEST_OPTIMIZATION, a FORTRAN90 code which defines test problems for the minimization of a scalar function of several variables, as described by Molga and Smutnicki.

toms611_test

Author:

David Gay

Reference:

  1. Alan Cline, Cleve Moler, Pete Stewart, James Wilkinson,
    An estimate for the Condition Number of a Matrix,
    Technical Report TM-310,
    Argonne National Laboratory, 1977.
  2. John Dennis, David Gay, Roy Welsch,
    Algorithm 573: An Adaptive Nonlinear Least-Squares Algorithm,
    ACM Transactions on Mathematical Software,
    Volume 7, Number 3, September 1981, pages 367-383.
  3. John Dennis, Howell Mei,
    Two New Unconstrained Optimization Algorithms Which Use Function and Gradient Values,
    Journal of Optimization Theory and Applications,
    Volume 28, 1979, pages 453-482.
  4. John Dennis, Jorge More,
    Quasi-Newton Methods, Motivation and Theory,
    SIAM Review,
    Volume 19, Number 1, January 1977, pages 46-89.
  5. David Gay,
    Algorithm 611: Subroutines for Unconstrained Minimization Using a Model/Trust Region Approach,
    ACM Transactions on Mathematical Software,
    Volume 9, Number 4, December 1983, pages 503-524.
  6. David Gay,
    Computing Optimal Locally Constrained Steps,
    SIAM Journal on Scientific and Statistical Computing,
    Volume 2, Number 2, June 1981, pages 186-197.
  7. Donald Goldfarb,
    Factorized Variable Metric Methods for Unconstrained Optimization,
    Mathematics of Computation,
    Volume 30, Number 136, October 1976, pages 796-811.
  8. Steven Goldfeld, Richard Quandt, Hale Trotter,
    Maximization by Quadratic Hill-climbing,
    Econometrica,
    Volume 34, 1966, pages 541-551.
  9. Michael Hebden,
    An Algorithm for Minimization Using Exact Second Derivatives,
    Technical Report: TP 515, Theoretical Physics Division,
    AERE Harwell, 1973.
  10. Jorge More,
    The Levenberg-Marquardt Algorithm, Implementation and Theory,
    in Springer Lecture Notes in Mathematics, Number 630,
    edited by GA Watson,
    Springer, 1978,
    LC: QA3.L28 Number 630.
  11. Jorge More, Danny Sorensen,
    Computing a Trust Region Step,
    Technical Report ANL-81-83,
    Argonne National Laboratory, 1981.
  12. Michael Powell,
    A Hybrid Method for Nonlinear Equations,
    in Numerical Methods for Nonlinear Algebraic Equations,
    edited by Philip Rabinowitz,
    Gordon and Breach, 1970,
    ISBN13: 978-0677142302,
    LC: QA218.N85.
  13. Michael Powell,
    A Fortran Subroutine for Solving Systems of Nonlinear Algebraic Equations,
    in Numerical Methods for Nonlinear Algebraic Equations,
    edited by Philip Rabinowitz,
    Gordon and Breach, 1970,
    ISBN13: 978-0677142302,
    LC: QA218.N85.
  14. Pete Stewart,
    A Modification of Davidon's Minimization Method to Accept Difference Approximations of Derivatives,
    Journal of the ACM,
    Volume 14, Number 1, January 1967, pages 72-83.
  15. Richard Varga,
    Minimal Gerschgorin Sets,
    Pacific Journal of Mathematics,
    Volume 15, 1965, pages 719-729.

Source Code:

Last revised on 14 March 2021.