OR/MS Today, June 1998

1998 Nonlinear Programming
Software Survey






Page 6



 
Product Publisher Restrictions Object
or Source Code
Derivative Calculation Requirements
AIMMS Paragon Decision Technology B.V. Differentiable constraints No None; Analytic derivatives are automatically computed by AIMMS.
CONOPT ARKI Consulting & Development A/S The model must be smooth and differentiable. It is assumed to be large and sparse. Object code (subroutine library);Executable modules w/ modeling languages. User must provide derivatives; they must be returned in sparse format and must be accurate.
CONOPT for AMPL Compass Modeling Solutions Differentiable and continuous (preferred) Object None - automatic differentiation
DFNLP K. Schittkowski Differentiable model functions Fortran source code Analytical or numerical
DOC/DOT Vanderplants R&D Inc. Continuous with continuous first derivatives Object user may provide; otherwise, finite differentiation is used
FANPAC/NLP Aptech Systems Inc. Twice differential objective function, P.D. Hession Source Numerical or user-supplied analytical
GRG2 Optimal Methods Inc. None, but best with a differentiable function Source code None
GRG2 for AMPL and AMPL Plus Compass Modeling Solutions Differentiable and continuous (preferred) Object None - automatic differentiation
IMSL Libraries Visual Numetrics None Both Either user-supplied or finite difference approximations are applied.
INTPT Optimal Methods Inc. None, but best with differentiable functions Source None
LANCELOT P. Toint Differentiability Source First derivatives (second if possible)
LGO, for Continuous Global Optimization Pinter Consulting Services Only continuity is assumed; applicable even to stand-alone, black box models Object None
LINGO LINDO Systems Inc. All standard math. functions and probability/queuing functions supported. Convexity & differentiability help, but not required. PC versions include DLL & OLE interfaces. None; Derivatives are calculated automatically; user can override defaults.
LSGRG for AMPL and AMPL Plus Compass Modeling Solutions Differentiable and continuous (preferred) Object None - automatic differentiation
LSGRG2 Optimal Methods Inc. None, but best with a differentiable function Source None
LSSOL Stanford Business Software Positive definite or semi-definite QP (including LP) linear constraints Source
Mathcad MathSoft Inc. Differentiable functions Object None
Microsoft Excel 97 - Solver Microsoft Corporation None, but convergence results depend on differentiability Object None
MINOS for AMPL Compass Modeling Solutions Differentiable and continuous (preferred) Object None - automatic differentiation
MINOS 5.5 Stanford Business Software Nonlinear objectives and constraint functions must be smooth, local optimum obtained for nonconvex problems. Source, Mex files for MATLAB Automatic or user supply
NAG C Library Numerical Algorithms Group Will use first derivatives if provided, but will estimate otherwise Both May provide first derivative, but not required
NAG Fortran Library Numerical Algorithms Group Will use first derivatives if provided, but will estimate otherwise Both May provide first derivative, but not required
NLPQL K. Schittkowski Differentiable model functions Fortran source code Analytical or numerical
NPSOL 5.0 Stanford Business Software Non-linear objective and constraints functions must be smooth. Local optimum obtaines for non-convex problems. Source, Mex files for MATLAB Automatic or user supply
Optimal EngineerĘ Transpower Corporation None Only under very special conditions None - program does it
Premium Solver Platform for Excel Frontline Systems Inc. None, but convergence results depend on differentiability Object None
Premium Solver, Premium Solver Plus for Excel Frontline Systems Inc. None, but convergence results depend on differentiability Object None
SAS Software SAS Institute Inc. Continuous objective with continuous 1st-order deriv. (except N-M simplex) Some techniques require continuous 2nd-order deriv. n Can compute deriv. via analysis or finite differentiation approx., or user can supply exact or approx. numerical functions.
SCIENTIST for Windows MicroMath Research n/a n/a n/a
SLP/GRG Optimal Methods Inc. None, but best with differentiable functions Source code None
SOCS and NLPSPR Boeing Co. Differentiable (C squared) Object code Analytic or finite difference derivatives
Solver DLL V3.0, Solver DLL Plus Frontline Systems Inc. Problem functions should be differentiable. Object code (Dynamic Link Library) User may optionally write jacobian subroutine to compute derivatives
Solver for Lotus 1-2-3 97/98 Frontline Systems Inc. None, but convergence results depend on differentiability Object code None
SOPT-CP SAITECH Inc. For convex problems, SOPT finds a global optimum. Otherwise, local optimum. Yes Without AMPL, need to set up Hession and/or Jacobian.
SQP Optimal Methods Inc. None, but best with differentiable functions Source code None
What's Best! LINDO Systems Inc. All standard math. functions & probability/queuing functions supported. Convexity & differentiability help, but not required. None; Derivatives are calculated automatically; user can override defaults.
XPRESS Barrier QP Solver Dash Associates Ltd. Convex quadratic objective and constraints allowed Object code only None
X Solver 2.0 Exatech Corporation None No No derivative calculations are used.

Nonlinear Programming Software Survey Pages:
Introduction | Page 1 | Page 2 | Page 3 | Page 4 | Page 5 | Page 6 | Page 7 | Page 8 | Accompanying Article
 


E-mail to the Editorial Department of OR/MS Today: orms@lionhrtpub.com


OR/MS Today copyright © 1998 by the Institute for Operations Research and the Management Sciences. All rights reserved.


Lionheart Publishing, Inc.
2555 Cumberland Parkway, Suite 299, Atlanta, GA 30339 USA
Phone: 770-431-0867 | Fax: 770-432-6969
E-mail: lpi@lionhrtpub.com
URL: http://www.lionhrtpub.com


Web Site © Copyright 1998 by Lionheart Publishing, Inc. All rights reserved.
Web Design by Premier Web Designs, e-mail lionwebmaster@preweb.com