Optimize Your Decisions with AMPL’s Linear Solver Partners
Gurobi efficiently handles non-convex mixed-integer programming (MIP) challenges, finding globally optimal solutions. Integrated with AMPL’s enhanced solver interface, Gurobi users benefit from streamlined model translation, automatic reformulation, and solver-specific performance optimizations. Widely used in finance, logistics, energy, and manufacturing, Gurobi—when paired with AMPL—delivers a seamless and highly efficient optimization workflow for large-scale, real-world problems.
CPLEX is a world-class solver for linear programming (LP) and mixed-integer programming (MIP), known for its speed and robustness. When integrated with AMPL, CPLEX benefits from automatic model reformulation, solver-aware preprocessing, and advanced tuning options, enabling users to achieve faster and more reliable solutions with minimal manual adjustments.
MOSEK is a high-performance solver specializing in LP, MIP, and conic optimization. With AMPL’s enhanced solver interface, MOSEK benefits from seamless problem formulation, automatic scaling, and solver-aware optimizations, ensuring efficient handling of large-scale optimization problems in finance, engineering, and machine learning.
XPRESS is a powerful linear and mixed-integer solver designed for high-speed optimization. AMPL’s tailored integration enhances XPRESS with automated preprocessing, solver-aware tuning, and flexible model handling, allowing users to efficiently solve large, complex problems in logistics, scheduling, and operations research.
COPT is a modern optimization solver focused on linear and mixed-integer programming, offering competitive performance across industries. AMPL’s solver interface enhances COPT with automatic reformulation, warm-start capabilities, and efficient constraint handling, making it a strong choice for large-scale industrial applications.
HiGHS is a cutting-edge open-source solver for LP and MIP, offering competitive performance in large-scale optimization. AMPL’s integration streamlines HiGHS with automatic model translation, solver-aware optimizations, and seamless workflow support, making it an accessible and efficient solution for diverse optimization needs.
CBC is a leading open-source solver for mixed-integer linear programming (MILP), providing flexibility for complex decision-making models. When used with AMPL, CBC benefits from automatic problem scaling, seamless solver interaction, and enhanced model preprocessing, ensuring a smooth and efficient optimization experience.
Maximizing Solver Performance with AMPL MP
AMPL MP is more than just a solver integration tool – it’s as bridge that enhances solver performance and usability within AMPL. Unlike raw solver interfaces, AMPL MP provides a unified, solver-agnostic framework that allows users to maximize solver efficiency without manual model adjustments. With built-in features like automatic reformulation and advanced solver interactions, AMPL MP ensures seamless, high-performance optimization for a wide range of problem types.
AMPL MP provides enhanced interfaces that refine how solvers interact with your models, ensuring greater efficiency and usability.
Choose from a wide range of supported solvers without needing to modify your models to fit vendor-specific requirements.
AMPL MP reformulates constraints and expressions automatically to align with the capabilities of each solver, reducing manual tuning and errors.
Features like warm starts, problem pre-processing, and solver-specific enhancements allow models to solve faster with less setup.
AMPL MP ensures that solvers built for AMPL are not just vendor solvers in their raw form. Instead, AMPL's solver interfaces provide additional optimizations, allowing you to achieve more without altering your models.
Rather than requiring users to modify models manually, AMPL MP reformulates problem structures dynamically—ensuring the best possible compatibility and performance for each solver.
From warm starts to solver-specific tuning, AMPL MP unlocks powerful solver capabilities with minimal configuration, letting you focus on modeling instead of technical adjustments.
Key industries and use cases leveraging linear solvers
Optimize power production and distribution, balance supply and demand, and reduce operational costs.
Enhance route planning, inventory management, and resource allocation to improve efficiency and reduce costs.
Develop optimal investment portfolios, risk management strategies, and financial forecasting models.
Streamline production schedules, minimize waste, and optimize resource utilization.
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.