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Get full MIP/LP/QP solving capabilities at a better price. This specialized license excludes extra tooling like OPL, since AMPL replaces it as the modeling layer—giving you exactly what you need to deploy CPLEX effectively.
AMPL makes it easier to formulate and maintain complex models. Send large-scale problems to CPLEX with no custom scripting or solver-specific reformulations.
Use CPLEX your way—on desktop, in the cloud, or embedded in enterprise systems. We provide licenses and support tailored to your environment and infrastructure.
As an official CPLEX reseller since 2014, AMPL gives you a powerful modeling environment purpose-built for large-scale, production-grade optimization. Use AMPL to design, test, and deploy your CPLEX-based models faster, without needing to rewrite code for every solver or system.
We make it faster, easier, and more cost-effective to get started with CPLEX.
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 - 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
CPLEX can be used with AMPL from various programming languages using our dedicated APIs
For Python enthusiasts, CPLEX 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 cplex # install CPLEX
# 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="cplex", cplex_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.
CPLEX excels in solving large-scale optimization problems across various domains, including logistics, supply chain management, finance, manufacturing, and energy. It’s particularly effective for problems involving complex decision-making processes and large datasets.
CPLEX can be used from several programming languages via AMPL APIs, including Python, R, Java, C++, C# and MATLAB. This flexibility allows users to integrate CPLEX into a wide range of applications and software environments.
Yes, CPLEX can be integrated with various data analysis and machine learning tools. Its compatibility via AMPL with popular programming languages and data science platforms enables seamless integration in complex data-driven optimization projects.
Key features of CPLEX include advanced presolving techniques, parallel processing capabilities, robust branch-and-cut algorithms for MIP, and specialized heuristics for quickly finding feasible solutions. These features collectively enhance its efficiency and solution quality.
CPLEX supports business decision-making by providing optimized solutions to complex problems. It helps companies reduce costs, improve operational efficiency, and make strategic decisions based on accurate, data-driven insights. Whether it’s optimizing supply chains, managing financial risks, or planning production, CPLEX provides a solid foundation for informed decision-making.