Optimization & simulation · AMPL Optimization Inc.

AMPL

Algebraic modeling language for describing optimization problems and sending them to a solver.

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AMPL is a modeling language, not a solver: it gives analysts a concise algebraic syntax for expressing variables, constraints and objectives, separate from the numerical method used to solve them. A model written in AMPL is passed to one of many interchangeable solvers — Gurobi, CPLEX, FICO Xpress, open-source options such as HiGHS and CBC, or specialized nonlinear and global solvers — without rewriting the model. This separation lets teams prototype in a smaller solver and move to a faster commercial one without touching the formulation. AMPL is used in operations research, energy, logistics and academic teaching, is available as a Python and cloud API as well as a standalone system, and is licensed commercially with a free academic option and a time-limited community edition.

At a glance

Vendor AMPL Optimization Inc.
Pricing model Subscription
Free tier Yes
Deployment Cloud, Self-hosted
Open source No
Best for Operations research teams and academics who want to formulate optimization problems once and test them against multiple solvers.

Pricing

Development licenses for the AMPL system and each solver are priced separately from about $300/month and $105/month respectively (billed annually); custom enterprise pricing; free community edition with open-source solvers and a free academic license.

Plan Price Notes
AMPL Development License from $300/month Billed annually
Solver add-ons from $105/month Priced per solver, billed annually; e.g. IBM CPLEX $400/month, Mosek $105/month
Enterprise Custom quote Multi-user, compute-based pricing, static or dynamic licenses
Community Edition Free Unrestricted access bundled with open-source solvers only

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features

  • Concise algebraic syntax for variables, constraints and objectives
  • Solver-agnostic: switch solvers without rewriting the model
  • Python, R and cloud APIs alongside the standalone system
  • Sensitivity analysis and automatic differentiation for nonlinear models
  • Set- and index-based data handling for large-scale models
  • Integration with Jupyter notebooks
  • Command-line and scripting interface for batch runs

Integrations

Profile last reviewed September 21, 2026

Alternatives

Pyomo Open-source Python library for formulating optimization models and sending them to a solver. Gurobi Optimizer Commercial mathematical solver for linear, mixed-integer and quadratic optimization problems. IBM ILOG CPLEX Optimization Studio IBM's commercial solver and modeling studio for linear, mixed-integer, quadratic and constraint programming.

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Terms to know

Prescriptive analytics Analytics that recommends specific actions by combining predictions with optimization or decision rules. What-if analysis Testing how a model's output changes when one or more input assumptions are changed, to explore specific alternative outcomes.

Related guides

How to choose an optimization or simulation tool Solvers compute one best answer to a math problem; simulators show how a system behaves over time. Pick the discipline before the vendor.