A proven choice for highly nonlinear problems, CONOPT’s efficient and reliable multi-method architecture handles a broad range of models. Specialized techniques achieve feasibility quickly, while powerful preprocessing tools reduce problem size and suggest formulation improvements.
Linear, quadratic, and general smooth nonlinear objectives and constraints in continuous variables.
Dynamic selection among feasible-path generalized reduced gradient, sequential quadratic programming, and sequential linear programming.
Extensions to the basic algorithms take advantage of second derivatives and identify feasible solutions more reliably.
CONOPT for AMPL is a specialized version of the solver, designed exclusively for use within the AMPL environment. It includes key enhancements that make the solver even more powerful, allowing it to handle large-scale nonlinear optimization problems with greater efficiency and speed.
CONOPT for AMPL is more than just a solver—it’s an enhanced nonlinear optimization experience. AMPL provides a purpose-built solver interface that allows CONOPT to efficiently solve large-scale smooth nonlinear programming (NLP) problems, even those with highly complex constraint structures. By leveraging AMPL’s modeling language, users gain faster insights, improved workflow efficiency, and a better return on their solver investment, all while maintaining the flexibility and power of CONOPT.
AMPL’s solver interface optimizes problem structures before they reach the solver, reducing computation time and improving efficiency. By automatically restructuring nonlinear models, AMPL enables CONOPT to solve large and highly constrained NLPs faster and more effectively, making complex decision-making problems more scalable.
One of AMPL’s key advantages is its ability to automatically reformulate nonlinear problems into solver-friendly formats. This ensures that even highly complex models with large constraint matrices and intricate dependencies are structured in a way that CONOPT can process more efficiently, improving solver stability and convergence speed.
To help users get the most out of CONOPT, AMPL offers consulting services and dedicated support plans for solver tuning and model optimization. Our experts provide solver diagnostics, advanced tuning, and optimization strategies to improve computation times and solver performance. Whether refining a problem formulation or troubleshooting solver behavior, AMPL’s specialized services ensure users achieve the best possible results with CONOPT.
Access this world-class solver in the AMPL License Portal, available on Windows, Linux, and macOS
CONOPT can be used with AMPL from various programming languages using our dedicated APIs
For Python enthusiasts, CONOPT 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 conopt # install CONOPT # Activate your license (e.g., free ampl.com/ce or ampl.com/courses licenses): $ python -m amplpy.modules activate <your-license-uuid>
How to use:
from amplpy import AMPL
ampl = AMPL()
...
ampl.solve(solver="conopt", conopt_options="option1=value1 option2=value2")For learning optimization and benchmarking solvers – a one-time 1 month free trial of CONOPT is available with a free Community Edition license.
For building and testing optimization models with commercial solver integration and full support, ensuring a smooth path to enterprise deployment.
AMPL starting at
$300 / month
Billed annually, includes updates and basic support.
CONOPT starting at
$145 / month
Billed annually, includes updates and basic support.
Build a custom plan – designed for large teams, multiple processes, high computational demands, or unique workflows.
All custom licenses built to your specific needs.
AMPL empowers businesses across diverse industries to make smarter decisions, improve efficiency, and maximize performance through optimization. From supply chain logistics to financial modeling, our expertise helps organizations tackle real-world challenges with precision and speed.
AMPL and CONOPT are widely used in agriculture, food production, and resource planning, helping organizations optimize land use, fertilizer distribution, and production schedules. With powerful nonlinear optimization capabilities, CONOPT helps farmers and agribusinesses maximize yields while minimizing costs and environmental impact.
CONOPT excels in chemical process optimization, reaction kinetics modeling, and production scheduling. With AMPL’s solver enhancements, companies in pharmaceuticals, petrochemicals, and industrial manufacturing can optimize resource allocation, improve yield, and minimize energy consumption in complex production systems.
AMPL and CONOPT help energy providers optimize power generation, distribution, and resource utilization, particularly in renewable energy and environmental impact analysis. These tools support efficient planning for energy grids, emissions reduction strategies, and sustainable resource management.
Get the most out of CONOPT with these essential resources—documentation, tutorials, and expert guides to help you optimize efficiently.
CONOPT for AMPL Documentation
Your go-to reference for using CONOPT, covering everything from installation to advanced solver techniques.
CONOPT Parameters & Options
Fine-tune CONOPT’s performance with a full list of solver parameters and configuration options.
MP Modeling Guide
Learn how to use the AMPL MP library to create flexible, solver-agnostic optimization models that work seamlessly with CONOPT.
CONOPT for AMPL on Google Colab
Run CONOPT with AMPL directly in your browser using pre-configured Google Colab notebooks—no installation required.
CONOPT for AMPL Change Log
Stay up to date with the latest improvements, bug fixes, and feature updates for the CONOPT-AMPL interface.
How to Use CONOPT for AMPL
Best practices for setting up CONOPT with AMPL, running models, and optimizing solver performance.
CONOPT is a powerful solver specifically designed for tackling large-scale nonlinear optimization problems. This includes problems with continuous variables where the objective function and/or constraints involve non-linear relationships.
The combination of CONOPT and AMPL offers several advantages:
No. AMPL, as an algebraic modeling language, allows you to define your optimization problem in a clear, human-readable format, eliminating the need for complex coding.
CONOPT offers various features to enhance problem-solving, including:
AMPL provides extensive documentation and tutorials specifically dedicated to using CONOPT. You can find resources on the AMPL website, including examples, user guides, and FAQs.
AMPL provides extensive documentation and tutorials specifically dedicated to using CONOPT. You can find resources on the AMPL website, including examples, user guides, and FAQs.
Access a complete optimization application building platform with simple pricing, or work with our team to design a custom package specifically for your business needs.
Get in touch to book a time for us to talk about your specific needs, and demo real solutions.
From startups to Fortune 500s, explore how industry-leading companies use AMPL to optimize complex problems.