Users Guide for SnadiOpt: A Package Adding Automatic Differentiation to Snopt

TL;DR

SnadiOpt integrates automatic differentiation with Snopt to simplify derivative computation in large-scale optimization problems, reducing manual coding effort and errors.

Contribution

It introduces a package that automatically generates derivative code for Snopt using ADIFOR, streamlining the optimization setup process.

Findings

Reduces manual derivative coding time.

Minimizes errors in derivative evaluation.

Facilitates large-scale nonlinear optimization.

Abstract

SnadiOpt is a package that supports the use of the automatic differentiation package ADIFOR with the optimization package Snopt. Snopt is a general-purpose system for solving optimization problems with many variables and constraints. It minimizes a linear or nonlinear function subject to bounds on the variables and sparse linear or nonlinear constraints. It is suitable for large-scale linear and quadratic programming and for linearly constrained optimization, as well as for general nonlinear programs. The method used by Snopt requires the first derivatives of the objective and constraint functions to be available. The SnadiOpt package allows users to avoid the time-consuming and error-prone process of evaluating and coding these derivatives. Given Fortran code for evaluating only the values of the objective and constraints, SnadiOpt automatically generates the code for evaluating the derivatives and builds the relevant Snopt input files and sparse data structures.