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.

An arcade-style TSP challenge game written for https://github.com/tunnuz/arcadetsp's 2018 Christmas Party, follow the in-game instructions.

Course about basic modeling for discrete optimization with MiniZinc

Learn supply chain principles through a visual simulation.

The CVRPLIB team announces the CVRPLIB BKS Challenge, a 30-day competition aimed at finding extremely high-quality solutions for the new XL benchmark set, 100 challenging CVRP instances ranging from 1,000 to 10,000 customers.

Web-based app that is intended to act as an entry point for data scientists and problem solvers who could benefit from optimization; the game teaches players why optimization is valuable and important, why it’s difficult (by showcasing the scaling and added complexity of optimization throughout round play), and why solvers and other optimization algorithms are essential in finding an optimal solution.

The CG:SHOP Challenge (Computational Geometry: Solving Hard Optimization Problems) is an annual competition dedicated to tackling specific, difficult geometric optimization problems. Originally established as a workshop at Computational Geometry Week (CG Week) in 2019, the Challenge provides a unique platform where the success of proposed solutions is measured based on computational performance on a set of carefully selected benchmark instances. This focus on empirical evaluation marks a shift from traditional computational geometry research, which often emphasizes theoretical approaches.

Consortium for Mathematics and its applications

COMAP's Mathematical Contest in Modeling (MCM) and Interdisciplinary Contest in Modeling (ICM) are international contests for high school students and college undergraduates. The contests challenge teams of up to three students to analyze, model, solve, and present solution reports to an open-ended application problem. In these contests research, analytics, and applied intelligence are just as important as time management and problem selection. Are you and your team up to it?

A game to better understand how CVRP works.

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.

Community for Decision Management, including Machine Learning and Optimization

Challenges from the Center for Discrete Mathematics and Theoretical Computer Science

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.

Grid Optimization challenges for electric systems

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.

Challenges around TSP variant with Santa Claus

The 2026 Land-Doig MIP Competition is a computational competition hosted by the 2026 Mixed Integer Programming Workshop, offering an opportunity for teams to showcase their practical and computational prowess and fostering innovation in computational MIP. It is named in honor of Ailsa H. Land and Alison G. Harcourt (née Doig), who proposed the first LP-based branch-and-bound algorithm.

Interactive resources to learn Graph Theory.

Interactive resources to learn OR.

The TLC is a simple constrained integer program turned into a game that you can play in a classroom with Legos. In each round of the game, your team acts as a boutique woodworking company who must decide which items to build and sell to the market. The goal is to decide how many of each type of item to build to maximize profits and beat other teams, where you are constrained by how many component pieces you have available.

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.

Annual challenges from the University of Lehigh

Challenges with different optimization problems

Developed to help spark an interest for mathematics in children and young adults. I use optimization concepts in the context of real-life problems as motivation. All you need are a printer to print the pages with the instructions and a pair of scissors to cut out the game pieces.

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.

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

Challenge from Parameterized Algorithms and Computational Experiments Challenge to bridge the gap between theory and practice of algorithms

Seems some of us can't see a problem without wanting to take a crack at solving it. Does that sound like you? Good. Forge ahead and ponder this month's problem. We'll post a new one every month, and allow a month for you to submit solutions (we may even publish submitted answers, especially if they're correct).

An LP modeler written in Python

A comprehensive guide to mathematical modeling with more than 140 games as case studies.

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.

Bi-annual challenges from the French Operational Research (OR) and Decision Support Society. 2026: https://gitlab.com/Orange-OpenSource/network-optimization-tools/challenge-roadef-2026/-/tree/main/sprint_results

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

Annual challenges organized by Shell AI team.

Deliver 100 barrels to the customer at the lowest cost. Select wells and refineries to choose volume flowing on pipe-lines.

Optimization competition organized by the Mexican Society of Operations Research (SMIO).

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

Learn about cutting planes in an adictive way.

A game to play the Knapsack to learn how to solve it.

Another game with map visualizations for the TSP.

Solve the TSP in a visual way from the Productions and Operations Management (Universitat Wein).

Vehicle Routing and Logistics work group from EURO