AMPL provides unified modeling, modern APIs, and enterprise deployment across commercial and open-source solvers.
AMPL provides unified modeling, modern APIs, and enterprise deployment across commercial and open-source solvers.
Write your optimization model once and run it across leading commercial and open-source solvers without restructuring your formulation. AMPL separates modeling from the solution engine, giving you flexibility without duplication.
Evaluate performance, licensing, or deployment trade-offs by switching solvers directly from the same model. No reformulation, no translation layers – just consistent execution across engines.
AMPL’s MP framework provides modern, consistent solver interfaces with advanced feature support, including callbacks, warm starts, solution pools, and detailed solver diagnostics.
Optimize performance with systematic benchmarking across solvers and parameter configurations. AMPL supports structured testing, reproducible experiments, and solver parameter tuning for large-scale production models.
Streamline procurement and deployment with consolidated solver licensing options, centralized support, and coordinated technical assistance across the optimization stack.
Integrate optimization into data science and production workflows using Python APIs and modern development environments. Connect models to databases, analytics pipelines, cloud infrastructure, and enterprise systems.
Gurobi delivers high-performance mixed-integer and nonconvex optimization. Integrated through AMPL’s unified interface, it supports seamless model execution, advanced reformulations, and solver-specific performance enhancements for large-scale applications.
CPLEX delivers high-performance linear and mixed-integer optimization with strong robustness and scalability. Integrated through AMPL’s unified interface, it supports automatic reformulation, solver-aware preprocessing, and advanced parameter tuning.
MOSEK delivers high-performance LP, MIP, and conic optimization with strong numerical stability. Integrated through AMPL’s unified interface, it supports seamless formulation, automatic scaling, and solver-aware performance enhancements.
Xpress delivers high-performance linear and mixed-integer optimization with strong scalability. Integrated through AMPL’s unified interface, it supports automatic preprocessing, solver-aware tuning, and efficient handling of large-scale models.
COPT delivers high-performance linear and mixed-integer optimization with strong scalability and modern algorithmic design. Integrated through AMPL’s unified interface, it supports automatic reformulation, warm starts, and efficient constraint handling for large-scale models.
Gurobi delivers high-performance mixed-integer and nonconvex optimization. Integrated through AMPL’s unified interface, it supports seamless model execution, advanced reformulations, and solver-specific performance enhancements for large-scale applications.
KNITRO delivers high-performance nonlinear optimization for large-scale and complex models. Integrated through AMPL’s unified interface, it supports solver-aware preprocessing, automatic differentiation, and advanced solver interactions for robust handling of constrained nonlinear problems.
CONOPT delivers reliable performance for large-scale nonlinear optimization, particularly in highly constrained models. Integrated through AMPL’s unified interface, it supports automatic model transformations and seamless solver integration for improved stability and efficiency.
LOQO delivers interior-point performance for nonlinear optimization with general constraints. Integrated through AMPL’s unified interface, it supports automatic reformulation and solver-aware tuning for efficient handling of large and complex models.
SNOPT delivers large-scale nonlinear optimization using sequential quadratic programming (SQP). Integrated through AMPL’s unified interface, it supports automatic scaling, warm starts, and refined solver interactions for efficient handling of complex constrained models.
MINOS delivers reliable performance for large, sparse nonlinear programming with smooth constraints. Integrated through AMPL’s unified interface, it supports automatic scaling and advanced solver integration for efficient handling of structured nonlinear models.
Gurobi delivers high-performance mixed-integer and nonconvex optimization. Integrated through AMPL’s unified interface, it supports seamless model execution, advanced reformulations, and solver-specific performance enhancements for large-scale applications.
BARON delivers global optimization for nonconvex problems with proven optimality guarantees. Integrated through AMPL’s unified interface, it supports enhanced preprocessing, automatic reformulation, and solver-aware tuning for efficient handling of large-scale mixed-variable models.
LGO delivers global optimization capabilities for problems with multiple local optima and limited structural assumptions. Integrated through AMPL’s unified interface, it supports automatic reformulation and seamless solver interaction for robust handling of complex nonconvex models.
LINDO Global delivers nonlinear and mixed-variable global optimization with support for both continuous and discrete models. Integrated through AMPL’s unified interface, it supports automatic problem adaptation and solver-aware enhancements for efficient handling of nonconvex and nonsmooth formulations.
HiGHS delivers high-performance open-source linear and mixed-integer optimization. Integrated through AMPL’s unified interface, it supports automatic model translation and solver-aware enhancements for efficient handling of large-scale models.
CBC delivers open-source mixed-integer linear optimization with flexibility for complex decision models. Integrated through AMPL’s unified interface, it supports automatic scaling and seamless solver interaction for efficient handling of MILP formulations.
IPOPT delivers large-scale nonlinear optimization using an interior-point method for smooth, constrained problems. Integrated through AMPL’s unified interface, it supports automatic reformulation and solver-aware tuning for efficient and scalable nonlinear model execution.
Bonmin delivers mixed-integer nonlinear optimization by combining branch-and-bound and interior-point methods. Integrated through AMPL’s unified interface, it supports automatic reformulation and solver-aware preprocessing for efficient handling of complex discrete–continuous models.
Couenne delivers open-source global optimization for nonconvex mixed-integer nonlinear programming problems with proven optimality guarantees. Integrated through AMPL’s unified interface, it supports automatic reformulation and solver-aware preprocessing for efficient handling of complex large-scale MINLP models.
Choosing the right solver can dramatically impact runtime, scalability, and total cost of ownership. AMPL provides structured evaluation and benchmarking services to help teams identify the best-performing solver configuration for their specific models and deployment environments.
We analyze formulation structure, sparsity patterns, integer density, nonlinear characteristics, and numerical scaling to determine which solver classes are most appropriate.
Run controlled experiments across multiple solvers using consistent datasets and performance metrics, including runtime, memory usage, solution quality, and stability.
Systematic solver parameter exploration to improve convergence speed, robustness, and repeatability for large-scale production models.
Stress testing under realistic data loads and deployment conditions to validate scalability and reliability before full rollout.
Contact us or download a free license, and start with commercial and open source solvers today.
Our resources provide you with the documentation needed to implement solvers.
Solver performance isn’t one-size-fits-all. AMPL makes it easy to compare solver performance objectively through benchmarking tools and services.
