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| Name of the Package | Author(s) | Purpose |
|---|---|---|
| BBVSCG | A.G. Buckley, A. Lenir | Unconstrained optimization,
Limited memory quasi-Newton method |
| BTN | Stephen G. Nash, George Mason University | Unconstrained nonlinear minimization for parallel computers. Suitable for large-scale optimization |
| CG DESCENT | William W. Hager, University of Florida, Department of Mathematics
Hongchao Zhang, University of Florida, Department of Mathematics | CG Papers and Software |
| CG+ | Guanghui Liu,
Jorge Nocedal, Northwestern University Richard Waltz, Northwestern University | CG+ is a Conjugate Gradient code for solving large-scale, unconstrained, nonlinear optimization problems.
CG+ implements three different versions of the Conjugate Gradient method: the Fletcher-Reeves method, the Polak-Ribiere method, and the positive Polak-Ribiere method (Beta always non-negative). |
| CONMIN | David Shanno, Rutgers University
K.H. Phua, National University of Singapore | Unconstrained optimization,
Limited memory CG method |
| HOOKE | Mark G. Johnson | Unconstrained minimization,
Searching method |
| LBFGS | Jorge Nocedal, Northwestern University,Ill. | Large-scale unconstrained minimization |
| LBFGSB | Ciyou Zhu, Richard Byrd, University of Colorado at Boulder
P.Lu-Chen, Jorge Nocedal, Northwestern University,Ill | Large-scale nonlinear optimization with simple bounds on variables |
| MINPACK | Jorge Moré, Argonne National Laboratory
Burt Garbow, Argonne National Laboratory Ken Hillstrom, Argonne National Laboratory | Nonlinear equations and Nonlinear least squares problems |
| SCALCG | Neculai Andrei, Research Institute for Informatics, Bucharest 1, Romania | Scaled Nonlinear Conjugate Gradient Method to find local minimizers of a differentiable function. |
| SCG | Ernesto Birgin, Institute of Mathematics and Statistics, University of São Paulo (USP), Brazil | Spectral Conjugate Gradient method to find local minimizers of a given function. |
| SUNDIALS | Radu Serban , Center for Applied Scientific Computing
Lawrence Livermore National Laboratory Livermore, California, USA | SUite of Nonlinear and DIfferential/ALgebraic equation Solvers consists of the following four solvers:
CVODE solves initial value problems for ordinary differential equation (ODE) systems. CVODES solves ODE systems and includes sensitivity analysis capabilities (forward and adjoint). IDA solves initial value problems for differential-algebraic equation (DAE) systems. KINSOL solves nonlinear algebraic systems. |
| TENMIN | Robert B. Schnabel , University of Colorado | Unconstrained optimization |
| TN | Stephen G. Nash, George Mason University | Large-scale unconstrained minimization |
| TNBC | Stephen G. Nash, George Mason University | Large-scale nonlinear optimization with simple bounds on variables |
| TNPACK | Tamar Schlick, Courant Institute of Mathematical Sciences
Aaron Fogelson, University of Utah | Nonlinear unconstrained minimization of large-scale separable problems |
| UNCMIN | Robert B. Schnabel , University of Colorado | Unconstrained optimization |
| UNO | Neculai Andrei, Research Institute for Informatics, Romania | Unconstrained Optimization,
Searching methods |
| VE08 | Ph. Toint, Department of Mathematics FUNDP Namur, BELGIUM | Bound constrained nonlinear optimization with an emphasis on large-scale problems |