MOSEK ApS provides optimization software that helps their clients make better decisions. Due to its powerful state-of-the-art simplex solver for linear problems and interior-point conic solver for quadratic and conic problems, MOSEK is widely employed in the technology, financial, energy and forestry industries.
Linear, quadratic and conic problems in continuous and integer variables.
Convex quadratic expressions in objectives and constraints; conic quadratic constraints; disjunctive constraints
For continuous problems, primal and dual simplex, interior-point (barrier); for integer problems, advanced branch-and-bound with presolve, feasibility heuristics and cut generators.
Shared-memory parallel processing for barrier, branch-and-bound. Tools to access remote optimization servers. Special facilities for infeasibility diagnosis.
MOSEK 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 larger, more complex optimization problems with greater efficiency and speed.
MOSEK for AMPL is more than just a solver—it’s an enhanced optimization experience. AMPL provides a purpose-built solver interface that allows MOSEK to handle large-scale convex optimization problems with greater efficiency and scalability. 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 MOSEK.
AMPL’s solver interface optimizes problem structures before they reach the solver, reducing computation time and improving efficiency. By intelligently restructuring mathematical programs, AMPL allows MOSEK to solve convex models faster and more effectively, making it easier to tackle large-scale decision-making challenges in finance, machine learning, and engineering.
One of AMPL’s key advantages is its ability to automatically reformulate problems into solver-friendly formats. This ensures that even highly complex convex optimization models are structured in a way that MOSEK can process more efficiently, improving convergence speed and solver stability. Whether handling semidefinite programming, second-order cone constraints, or large-scale linear programs, AMPL ensures MOSEK operates at its full potential.
To help users get the most out of MOSEK, 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 MOSEK.
Access this world-class solver in the AMPL License Portal, available on Windows, Linux, and macOS
Mosek can be used with AMPL from various programming languages using our dedicated APIs
For Python enthusiasts, Mosek 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 mosek # install MOSEK # 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="mosek", mosek_options="option1=value1 option2=value2")For learning optimization and benchmarking solvers – a one-time 1 month free trial of Mosek 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.
Mosek starting at
$55 / 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.
MOSEK and AMPL are widely used in financial optimization, particularly for portfolio management, risk minimization, and asset allocation. By leveraging MOSEK’s strength in convex optimization, financial firms can efficiently balance risk and return while ensuring compliance with complex regulatory constraints.
MOSEK’s powerful convex solvers make it an essential tool in machine learning, support vector machines, and AI model training. AMPL provides a seamless interface for structuring and optimizing large-scale ML problems, improving training efficiency and predictive accuracy across various applications.
AMPL and MOSEK are used in engineering and structural optimization to improve material efficiency, minimize costs, and ensure design stability. Industries such as aerospace, civil engineering, and manufacturing rely on MOSEK’s ability to handle complex convex models for load distribution, stress analysis, and structural performance optimization.
Get the most out of Mosek with these essential resources—documentation, tutorials, and expert guides to help you optimize efficiently.
Mosek for AMPL Documentation
Your go-to reference for using Mosek, covering everything from installation to advanced solver techniques.
Mosek Parameters & Options
Fine-tune Mosek’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 mosek.
Mosek for AMPL on Google Colab
Run Mosek with AMPL directly in your browser using pre-configured Google Colab notebooks—no installation required.
Mosek for AMPL Change Log
Stay up to date with the latest improvements, bug fixes, and feature updates for the Mosek-AMPL interface.
How to Use Mosek for AMPL
Best practices for setting up Mosek with AMPL, running models, and optimizing solver performance.
MOSEK excels at handling linear, mixed-integer linear, quadratic, and conic optimization problems. This includes complex challenges in finance, energy, transportation, scheduling, resource allocation, and design optimization.
MOSEK supports all major 64-bit operating systems (Windows, Linux, macOS) and integrates with various nl-based modeling languages and interfaces. This flexibility allows users to choose their preferred environment for working with MOSEK.
MOSEK is used by leading companies and organizations across various industries. For example, airlines use MOSEK to optimize route planning and aircraft scheduling, reducing fuel consumption and delays. Financial institutions leverage it for portfolio optimization and risk management, maximizing returns while minimizing risk exposure. In the energy sector, MOSEK helps optimize power grid operations and integrate renewable energy sources, contributing to sustainability and grid resilience.
MOSEK uses a combination of interior-point and simplex algorithms along with branch-and-bound methods for different problem types, ensuring efficient and reliable solutions.
MOSEK is designed to handle large and complex optimization problems with millions of variables and constraints. It utilizes advanced memory management and parallelization techniques for scalability.
AMPL’s integration with MOSEK provides advanced data connectivity options, enabling seamless access to databases and APIs for efficient data importation into optimization models and exporting results for analysis or system integration. This feature supports direct interaction with SQL databases via ODBC for real-time data queries, and custom scripts can facilitate API communication, allowing for dynamic data exchange. Such connectivity empowers users to incorporate real-time data into their AMPL models, optimize using MOSEK, and then directly update databases or interact with other services. This integration ensures that optimization processes are deeply embedded within data-driven decision-making frameworks, making the AMPL-MOSEK combo a powerful tool for applications requiring up-to-date data and comprehensive system integration.
MOSEK offers a large set of options to adjust its behaviour. Learn more here.
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.