KNITRO.jl

KNITRO.jl is a wrapper for the Artelys Knitro solver.

It has two components:

• a thin wrapper around the C API
• an interface to MathOptInterface.

Affiliation

This wrapper is maintained by the JuMP community with help from Artelys.

Contact Artelys support if you encounter any problem with this interface or the solver.

License

KNITRO.jl is licensed under the MIT License.

The underlying solver is a closed-source commercial product for which you must purchase a license.

Installation

First, obtain a license and install a copy of KNITRO from Artelys.

Then, install KNITRO.jl using the Julia package manager:

import Pkg
Pkg.add("KNITRO")

If you are having trouble installing KNITRO.jl, here are several things to try:

• Make sure that you have defined your global variables correctly, for example with export KNITRODIR="/path/to/knitro-vXXX-$OS-64" and export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$KNITRODIR/lib". You can check that KNITRO.jl sees your library with using KNITRO; KNITRO.has_knitro().
• If KNITRO.has_knitro() returns false but you are confident that your paths are correct, try running Pkg.build("KNITRO") and restarting Julia. In at least one user's experience, installing and using KNITRO in a temporary Julia environment (activated with ] activate --temp) does not work and the need to manually build is likely the reason why.

Use with JuMP

To use KNITRO with JuMP, use KNITRO.Optimizer:

using JuMP, KNITRO
model = Model(KNITRO.Optimizer)
set_attribute(model, "outlev", 1)
set_attribute(model, "algorithm", 4)

Use with AMPL

To use KNITRO with AmplNLWriter.jl, use KNITRO.amplexe:

using JuMP
import AmplNLWriter
import KNITRO
model = Model(() -> AmplNLWriter.Optimizer(KNITRO.amplexe, ["outlev=3"]))

Use with other packages

A variety of packages extend KNITRO.jl to support other optimization modeling systems. These include:

• NLPModelsKnitro
• Optimization.jl

MathOptInterface API

The Knitro optimizer supports the following constraints and attributes.

List of supported objective functions:

• MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}
• MOI.ObjectiveFunction{MOI.ScalarQuadraticFunction{Float64}}
• MOI.ObjectiveFunction{MOI.VariableIndex}

List of supported variable types:

• MOI.Reals

List of supported constraint types:

• MOI.ScalarAffineFunction{Float64} in MOI.EqualTo{Float64}
• MOI.ScalarAffineFunction{Float64} in MOI.GreaterThan{Float64}
• MOI.ScalarAffineFunction{Float64} in MOI.Interval{Float64}
• MOI.ScalarAffineFunction{Float64} in MOI.LessThan{Float64}
• MOI.ScalarQuadraticFunction{Float64} in MOI.EqualTo{Float64}
• MOI.ScalarQuadraticFunction{Float64} in MOI.GreaterThan{Float64}
• MOI.ScalarQuadraticFunction{Float64} in MOI.Interval{Float64}
• MOI.ScalarQuadraticFunction{Float64} in MOI.LessThan{Float64}
• MOI.VariableIndex in MOI.EqualTo{Float64}
• MOI.VariableIndex in MOI.GreaterThan{Float64}
• MOI.VariableIndex in MOI.Integer
• MOI.VariableIndex in MOI.Interval{Float64}
• MOI.VariableIndex in MOI.LessThan{Float64}
• MOI.VariableIndex in MOI.ZeroOne
• MOI.VectorAffineFunction{Float64} in MOI.SecondOrderCone
• MOI.VectorOfVariables in MOI.Complements
• MOI.VectorOfVariables in MOI.SecondOrderCone

List of supported model attributes:

• MOI.NLPBlock()
• MOI.NLPBlockDualStart()
• MOI.ObjectiveSense()

Options

A list of available options is provided in the KNITRO reference manual.

Low-level wrapper

KNITRO.jl implements most of Knitro's functionalities. If you aim at using part of Knitro's API that are not implemented in the MathOptInterface/JuMP ecosystem, you can refer to the low-level API, which wraps Knitro's C API (whose templates are specified in the file knitro.h).

Extensive examples using the C wrapper can be found in examples/.

Multi-threading

Due to limitations in the interaction between Julia and C, KNITRO.jl disables multi-threading if the problem is nonlinear. This will override any options such as par_numthreads that you may have set. Read GitHub issue #93 for more details.