16.01.2015 Views

GAMS — The Solver Manuals - Available Software

GAMS — The Solver Manuals - Available Software

GAMS — The Solver Manuals - Available Software

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

SNOPT<br />

Philip E. Gill; Department of Mathematics, University of California, San Diego, La Jolla, CA<br />

Walter Murray, Michael A. Saunders; Department of EESOR, Stanford University, Stanford, CA<br />

Arne Drud; ARKI Consulting and Development, Bagsvaerd, Denmark<br />

Erwin Kalvelagen; <strong>GAMS</strong> Development Corp., Washington DC<br />

Contents<br />

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 521<br />

1.1 Problem Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 522<br />

1.2 Selecting the SNOPT <strong>Solver</strong> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 522<br />

2 Description of the method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523<br />

2.1 Objective function reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523<br />

2.2 Constraints and slack variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524<br />

2.3 Major iterations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524<br />

2.4 Minor iterations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524<br />

2.5 <strong>The</strong> reduced Hessian and reduced gradient . . . . . . . . . . . . . . . . . . . . . . . . . 525<br />

2.6 <strong>The</strong> merit function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 526<br />

2.7 Treatment of constraint infeasibilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . 526<br />

3 Starting points and advanced bases . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527<br />

3.1 Starting points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527<br />

3.2 Advanced basis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529<br />

4 Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530<br />

4.1 <strong>GAMS</strong> options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530<br />

4.2 Model suffices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531<br />

4.3 SNOPT options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 532<br />

5 <strong>The</strong> SNOPT log . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 542<br />

5.1 EXIT conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547<br />

6 Listing file messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 550<br />

1 Introduction<br />

This section describes the <strong>GAMS</strong> interface to the general-purpose NLP solver SNOPT, (Sparse Nonlinear Optimizer)<br />

which implements a sequential quadratic programming (SQP) method for solving constrained optimization<br />

problems with smooth nonlinear functions in the objective and constraints. <strong>The</strong> optimization problem is assumed

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!