A Procedure for Computing Forward-Difference Intervals for Numerical Optimization.
Abstract
When minimizing a smooth nonlinear function whose derivatives are not available, a popular approach is to use a gradient method with a finite-difference approximation substituted for the exact gradient. In order for such a method to be effective, it must be possible to compute 'good' derivative approximations without requiring a large number of function evaluations. Certain 'standard' choices for the finite-difference interval may lead to poor derivative approximations for badly scaled problems. We present an algorithm for computing a set of intervals to be used in a forward-difference approximation of the gradient, and describe its implementation as a transportable Fortran subroutine.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1981
- Accession Number
- ADA111627
Entities
People
- M. H. Wright
- Mark A. Saunders
- P. E. Gill
- William J. Murray
Organizations
- Stanford University