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Trusted by thousands of industry leading teams
A streamlined Knitro license tailored for use with AMPL delivering full MIP/LP/QP solving power without extra tooling. Get exactly what you need at a better price.
AMPL’s solver interface handles large, complex models with no custom scripting or solver-specific rewrites.
Desktop, cloud, or on-prem. License what you need, when you need it.
AMPL and Knitro are trusted in energy, finance, logistics, and other high-stakes industries.
As a premier partner of Knitro since 2010, AMPL gives you a modeling environment built for large-scale, long-term optimization. Design, test, and deploy your Knitro-based models with greater speed and fewer internal resources.
We make it faster, easier, and more cost-effective to get started with Knitro
Full-featured solver access, configured for desktop, server, or cloud
A robust, declarative interface to simplify and scale your model development
For Python, Jupyter, AMPL MP, or command-line workflows, get solving fast
Optimization experts available for use-case benchmarks, tuning, and scaling
AMPL connects with Python, APIs, and your existing data pipelines with no workflow disruption
Access to solver engineers who understand both your model and your mission
Access this world-class solver in the AMPL License Portal, available on Windows, Linux, and macOS.
Knitro can be used with AMPL from various programming languages using our dedicated APIs.
For Python enthusiasts, Knitro is also accessible as a module with amplpy, blending seamlessly with your Python projects.
How to install using amplpy:
# Install Python API for AMPL:
$ python -m pip install amplpy --upgrade
# Install AMPL & solver modules:
$ python -m amplpy.modules install knitro # install knitro
# Activate your license:
$ python -m amplpy.modules activate <your-license-uuid>How to use:
from amplpy import AMPL
ampl = AMPL()
...
ampl.solve(solver="knitro", knitro_options="option1=value1 option2=value2")Choose a complete, optimized licensing solution or work with us to design a custom package that fits your environment and goals. We’ll help you configure, deploy, and scale faster.
Knitro is specifically designed for solving large-scale, complex non-linear optimization problems. It excels in areas like mixed-integer, quadratic, and nonlinear programming, making it ideal for applications in finance, energy management, engineering design, and more.
Knitro seamlessly integrates with AMPL, allowing users to define their optimization models in AMPL’s user-friendly language, which Knitro then solves using its advanced algorithms. This integration provides an efficient workflow for formulating, solving, and analyzing optimization problems.
Yes, Knitro is renowned for its ability to efficiently solve large-scale optimization problems. Its advanced algorithms and techniques are specifically designed to handle the complexities and size of real-world problems.
Knitro provides comprehensive documentation, including user guides, example problems, and technical references. Additionally, users have access to a dedicated support team for technical assistance and guidance in both using Knitro and integrating it with AMPL.
Yes, a trial version of Knitro is available for evaluation purposes. Prospective users can request a trial to assess Knitro’s capabilities to determine if it meets their specific optimization needs.
Knitro uses rigorously tested algorithms and numerical methods to ensure the accuracy and reliability of its solutions. It employs advanced techniques to verify solution quality and provides detailed diagnostic information to aid in model evaluation and troubleshooting.
Knitro stands out for its specialized focus on non-linear problems, its ability to handle a wide range of problem types, and its seamless integration with modeling languages like AMPL. Its robustness, speed, and advanced features make it a preferred choice for complex, non-linear optimization tasks.
Yes, Knitro is widely used in academic research for solving complex optimization problems across various disciplines. Special licensing options are available for academic institutions, supporting research and educational use.