Find your next solver
A curated index of Operations Research resources — solvers, courses, books, datasets, communities and more. Classified by type, topic and audience.
38 resources matching
- Advanced modeling for discrete optimizationCourse
Course about advanced modeling for discrete optimization, covering topics such as debugging or predicates
- AliGorithmVideo
YouTube channel with interesting knowledge about optimization.
- AMPLModeling language
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.
- Anything you can do I can do betterVideo
Prof Marco Lubbecke talks about optimization in a TED Talk.
- Basic modeling for discrete optimizationCourse
Course about basic modeling for discrete optimization with MiniZinc
- BKS ChallengeChallenge
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.
- CG:SHOPChallenge
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.
- COMAP contestsChallenge
Consortium for Mathematics and its applications
- COMAP mcm-icmChallenge
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?
- CVXPYModeling language
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.
- Decision Management Community challengesChallenge
Community for Decision Management, including Machine Learning and Optimization
- DIMACS challengeChallenge
Challenges from the Center for Discrete Mathematics and Theoretical Computer Science
- Discrete Optimization courseCourse
Course about discrete optimization covering a wide range of optimization techniques such as Constraint Programming, Local Search or Column Generation
- Free the world from wasteful scheduling with Timefold AIVideo
Solve NP-hard optimization problems with Timefold AI.
- GAMSModeling language
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.
- Google OR-ToolsModeling language
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 competitionChallenge
Grid Optimization challenges for electric systems
- JuMPModeling language
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.
- Kaggle Optimization ChallengesChallenge
Challenges around TSP variant with Santa Claus
- Land-Doig CompetitionChallenge
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.
- MathOpt: Solver Independent Modeling in Google OR-ToolsVideo
A new interface for Google OR-Tools.
- MiniZincModeling language
MiniZinc is a high-level constraint modelling language that allows you to easily express and solve discrete optimisation problems.
- ML ain’t your only hammerVideo
Introduction to the field of mathematical optimization.
- MOPTA challengeChallenge
Annual challenges from the University of Lehigh
- OPTIL.ioChallenge
Challenges with different optimization problems
- optlangModeling language
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.
- OR from 0 to 1Course
7-day free email course to kickstart in Operations Research.
- PACE challengeChallenge
Challenge from Parameterized Algorithms and Computational Experiments Challenge to bridge the gap between theory and practice of algorithms
- Pragmatic OR: Solving large scale optimization problems in fast moving environmentsVideo
Rubén Ruiz, Principal Applied Scientist at Amazon, shows how he leverages Hexaly at Amazon to solve a gigantic optimization problem that is out of the scope of other MILP solvers.
- PuLPModeling language
An LP modeler written in Python
- PyomoModeling language
Python-based, open-source optimization modeling language with a diverse set of optimization capabilities.
- PyOptInterfaceModeling language
PyOptInterface is an open-source Python library to provide a unified API to construct and solve optimization models with various optimizers.
- ROADEF challengeChallenge
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
- RWTHx: Mathematical Optimization for EngineersCourse
Course about all things mathematical optimization: unconstrained, LP, NLP, MIP, Global optimization, Dynamic optimization, ML for optimization, and optimization under uncertainty.
- Shell AI challengeChallenge
Annual challenges organized by Shell AI team.
- SMIO ChallengeChallenge
Optimization competition organized by the Mexican Society of Operations Research (SMIO).
- Solving algorithms for discrete optimizationCourse
Course about solving discrete optimization problems with different techniques: Constraint Programming, Mixed Integer Programming and Local Search
- VeRoLogChallenge
Vehicle Routing and Logistics work group from EURO