Find your next solver

Course about advanced modeling for discrete optimization, covering topics such as debugging or predicates

Welcome to AMPL (A Mathematical Programming Language), a powerful and intuitive modeling language designed specifically for large-scale optimization problems. If you are new to modeling languages or AMPL, this page will guide you through what AMPL is, its benefits, and why it stands out in the landscape of programming and modeling languages.

Course about basic modeling for discrete optimization with MiniZinc

CSPLib is a library of test problems for constraint solvers.

Instances for the CVRP challenge.

CVXPY is an open source Python-embedded modeling language for convex optimization problems. It lets you express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers.

Course about discrete optimization covering a wide range of optimization techniques such as Constraint Programming, Local Search or Column Generation

GAMS is a modeling system for mathematical optimization that lets users formulate complex problems in a high-level language and run them with different commercial and open-source solvers. All solvers are packaged in a single distribution, making it easy to switch between them and giving customers one point of contact for licensing and support. It also has a Python interface -GAMSPy- for building and solving mathematical optimization models using the GAMS technology stack. It keeps the modeling concepts of GAMS (sets, parameters, variables, equations) but exposes them as Python classes and functions. This allows modelers to stay in the Python ecosystem while using mature GAMS solvers and workflows.

Open source software suite for optimization, tuned for tackling the world's toughest problems in vehicle routing, flows, integer and linear programming, and constraint programming.

JuMP is a domain-specific modeling language for mathematical optimization embedded in Julia. JuMP makes it easy to formulate and solve a range of problem classes, including linear programs, integer programs, conic programs, semidefinite programs, and constrained nonlinear programs.

This site provides access to a number of Operations Research problem data sets.

MiniZinc is a high-level constraint modelling language that allows you to easily express and solve discrete optimisation problems.

An extensible framework for solving discrete optimization problems using a combination of Mixed-Integer Linear Programming (MIP) and Machine Learning (ML). MIPLearn uses ML methods to automatically identify patterns in previously solved instances of the problem, then uses these patterns to accelerate the performance of conventional state-of-the-art MIP solvers such as CPLEX, Gurobi or XPRESS.

Optlang is a Python package implementing a modeling language for solving mathematical optimization problems, i.e. maximizing or minimizing an objective function over a set of variables subject to a number of constraints. Optlang provides a common interface to a series of optimization tools, so different solver backends can be changed in a transparent way.

Instances for several interesting NP-hard problems.

7-day free email course to kickstart in Operations Research.

An LP modeler written in Python

Python-based, open-source optimization modeling language with a diverse set of optimization capabilities.

PyOptInterface is an open-source Python library to provide a unified API to construct and solve optimization models with various optimizers.

Instances for Quadratic Assignment Problems.

Course about all things mathematical optimization: unconstrained, LP, NLP, MIP, Global optimization, Dynamic optimization, ML for optimization, and optimization under uncertainty.

SNDlib is a library of data for Survivable fixed telecommunication Network Design. Its purpose is to provide data about realistic telecommunication networks (including traffic) available to the research community.

Course about solving discrete optimization problems with different techniques: Constraint Programming, Mixed Integer Programming and Local Search

OR-Library is a collection of test data sets for a variety of Operations Research (OR) problems.

TSPLIB is a library of sample instances for the TSP (and related problems) from various sources and of various types.

This web is dedicated to the study of VRP; we have compiled here a great deal of information about it for public access: technical reports, many different variants of the problem, alternative algorithms and techniques for solving it, some well-known instances of the problem, the best-so-far solutions for those instances, bibliography, related links…