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KNITRO

The NEOS Server offers KNITRO for the solution of general nonconvex, nonlinearly constrained optimization problems in AMPL format. KNITRO can also be effectively used to solve simpler classes of problems such as unconstrained problems, bound constrained problems, linear programs (LPs) and quadratic programs (QPs).

KNITRO offers both interior-point and active-set methods. Choose the algorithm you wish to use through the KNITRO/AMPL option "alg". The choices are as follows:

0: automatic algorithm selection
1: Interior/Direct algorithm
2: Interior/CG algorithm
3: Active algorithm

The default value is "alg=0" but we encourage the user to try all optimizers.

For a more complete description of KNITRO, see R. H. Byrd, J. Nocedal, and R. A. Waltz, KNITRO: An Integrated Package for Nonlinear Optimization , In G. di Pillo and M. Roma, editors, Large-Scale Nonlinear Optimization, 35-59, 2006. Springer Verlag.

KNITRO was developed by Richard Byrd, Mary Beth Hribar, Jorge Nocedal and Richard Waltz with additional help from Guanghui Liu, Marcelo Marazzi, Todd Plantenga and Jose Luis Morales.

KNITRO is sold through Ziena Optimization.

Additional information on KNITRO (including information on how to obtain KNITRO) can be found at the KNITRO website.


Using the NEOS Server for KNITRO

The user must submit a model in AMPL format to solve a nonlinearly constrained optimization problem. Examples of models in AMPL format can be found in the netlib collection.

The model is specified by a model file, and optionally, a data file and a commands file. Do not include the solve command in the model or data file. If a command file is specified it must contain the AMPL solve command; otherwise the solve command is invoked automatically by the Server.

The commands file can contain any AMPL command or set options for KNITRO, for example,

option knitro_options "maxit=50";

See the KNITRO options table for a list of options.

Printing directed to standard out is returned to the user with the output.


Enter the location of the ampl model (local file)
Model File:


Enter the location of the ampl data file (local file)
Data File:


Enter the location of the ampl commands file (local file)
Commands File:



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