Use AMPL FREE with open source solvers
Our Community Edition license allows you to use a fully-powered AMPL license with no limitations on variables or constraints for free, for personal, academic, and commercial prototyping purposes, including all open-source solvers. You can download AMPL Community Edition from our portal.
Start with an uploaded model, run and modify, or create your own with AMPL in Google Colab. Open source solvers are already connected. Call them and solve!
Powerful options for continuous and integer problems when speed can be compromised or smaller, simple projects.
The COIN Branch and Cut solver (CBC) is an open-source mixed-integer program (MIP) solver written in C++. CBC is an active open-source project led by John Forrest at www.coin-or.org.
HiGHS is open-source software to solve linear programming, mixed-integer programming, and convex quadratic programming models. Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, JavaScript, Fortran, and C#. It has no external dependencies.
SCIP is currently one of the fastest non-commercial solvers for mixed integer programming (MIP) and mixed integer nonlinear programming (MINLP). It is also a framework for constraint integer programming and branch-cut-and-price. It allows for total control of the solution process and the access of detailed information down to the guts of the solver.
GCG is a generic decomposition solver for mixed-integer programs (MIPs). It automatically performs a Dantzig-Wolfe reformulation and runs a full-fledged branch-price-and-cut algorithm to solve it to optimality. Alternatively, GCG is able to automatically apply a Benders decomposition. No user interaction is necessary, thus GCG provides decomposition-based MIP solving technology to everyone.
Your free alternatives for problems involving smooth nonlinear functions of powers, logs, and ratios with the most effectiveness in smaller problem sizes.
Ipopt (Interior Point Optimizer, pronounced “Eye-Pea-Opt”) is an open source software package for large-scale nonlinear optimization. The Ipopt package is available from COIN-OR under the EPL (Eclipse Public License) open-source license and includes the source code for Ipopt.
Bonmin is an experimental open-source C++ code for solving general MINLP problems.
Global optimization in the presence of multiple locally optimal solutions. Techniques for nonsmooth and discrete functions, and for highly combinatorial and/or logical constraints.
This page provides resources for Couenne (Convex Over and Under ENvelopes for Nonlinear Estimation), an Open Source branch&bound algorithm for solving Mixed-Integer Nonlinear Programming (MINLP) problems. Couenne aims at finding global optima of nonconvex MINLPs. It implements linearization, bound reduction, and branching methods within a Branch&Bound framework.
Handle constraint programming* problems in discrete variables with support of a wide variety of constraint types that may contain nonlinear and logical expressions.
* Constraint programming solvers can be more effective than MIP solvers for some kinds of combinatorial optimization problems.
Gecode is an open source C++ toolkit for developing constraint-based systems and applications. Gecode provides a constraint solver with state-of-the-art performance while being modular and extensible. Learn more here.
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These solvers all handle linear optimization problems in both continuous and integer variables. Their performance is not at the level of analogous commercial solvers, but can be sufficient for problems that are not too large or difficult.
2.10.5 – From COIN-OR under the Eclipse Public License; available as source code and binaries for 32-bit Linux, 64-bit Linux, OS X, 32-bit Windows and 64-bit Windows.
HiGHS
The solvers in this category seek solutions to problems involving smooth nonlinear functions such as powers, logs, and ratios. They differ in the algorithms that they offer, and hence in their effectiveness for different problem types. Due to the difficulty of nonlinear optimization, these solvers are effective with smaller problems than their linear counterparts.
3.12.13 — From COIN-OR under the Eclipse Public License; available as source code and binaries for 32-bit Linux, 64-bit Linux, macOS X, 32-bit Windows and 64-bit Windows. Finds locally optimal solutions to continuous nonlinear problems, using an interior-point method.
1.8.8 — from COIN-OR under the Eclipse Public License; available as source code and binaries for 32-bit Linux, 64-bit Linux, macOS X, 32-bit Windows and 64-bit Windows. Finds globally optimal solutions to convex nonlinear problems in continuous and discrete variables, and may be applied heuristically to nonconvex problems.
0.5.8 — from COIN-OR under the Eclipse Public License; available as source code and binaries for 32-bit Linux, 64-bit Linux, macOS X, 32-bit Windows and 64-bit Windows. Finds globally optimal solutions to nonlinear problems in continuous and discrete varia
These solvers handle constraint programming problems usually in discrete variables. They support a wide variety of constraint types that may contain nonlinear and logical expressions. Constraint programming solvers can be more efficient than MIP solvers for some kinds of combinatorial optimization problems.
Under the MIT license; available as source code and binaries for 32-bit Linux, 64-bit Linux, macOS X, 32-bit Windows and 64-bit Windows.
Under the GNU Affero General Public License; available as source code and binaries for 32-bit Linux, 64-bit Linux, macOS X, 32-bit Windows and 64-bit Windows.
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