Accession Number:

ADA123204

Title:

A Modular System of Algorithms for Unconstrained Minimization.

Descriptive Note:

Technical rept.,

Corporate Author:

COLORADO UNIV AT BOULDER DEPT OF COMPUTER SCIENCE

Report Date:

1982-11-01

Pagination or Media Count:

37.0

Abstract:

We describe a new package, UNCMIN, for finding a local minimizer of a real valued function of more than one variable. The novel feature of UNCMIN is that it is a modular system of algorithms, containing three different step selection strategies line search, dogleg, and optimal step that amy be combined with either analytic or finite difference gradient evaluation, and either analytic, finite difference, or BFGS Hessian approximation. We present the results of a comparison of the three step selection strategies on the problems in More, Garbow, and Hillstrom in two separate cases using finite difference gradients and Hessians, and using finite difference gradients with BFGS Hessian approximations. We also describe a second package, REVMIN, that uses optimization algorithms identical to UNCMIN but obtains values of user supplied functions by reverse communication. Author

Subject Categories:

  • Theoretical Mathematics
  • Computer Programming and Software

Distribution Statement:

APPROVED FOR PUBLIC RELEASE