Find your next solver

Decision Science Leader at Toyota sharing career development tips.

Advanced Analytics in Practice focusing on breaking down what it takes to build real-world advanced analytics applications.

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

AGI? No, thank you! Learning and Intelligent Optimization? Yes, please! https://intelligent-optimization.org/

Learn more about how AI is changing businesses and how you can leverage it: Insights, tools, tips, and expert voices

Case studies from AIMMS

Operations Research Engineer at Réseau de Transport d'Électricité that shares optimization knowledge in his YouTube channel, Aligorithm.

YouTube channel with interesting knowledge about optimization.

Lead Data Scientist at Bluecrux with a newsletter about Constraint Programming.

Sales at Gurobi, shares interesting posts about Gurobi.

Blog with news from the Operations Research and Optimization group at Amazon

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.

Optimization problems in businesses using AMPL

Associate Professor at Universidade Federal da Paraíba + Host of the “Subject to” podcast.

Optimization Expert | Algorithm Design | Operations Research

The journal publishes 24 issues a year that focus on the theoretical, practical, and computational aspects of operations research

Prof Marco Lubbecke talks about optimization in a TED Talk.

BARON is the industry-leading solver for mixed-integer nonlinear programming (MINLP).

Course about basic modeling for discrete optimization with MiniZinc

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.

Lead Operations Research Engineer at Trucksters with a newsletter about all things Operations Research.

PhD Operations Research | Lead Engineer @ FICO

Operations Research Scientist at Amazon, shares pragmatic views about delivering value through OR.

Co-Founder + CEO at Nextmv.

Operations Research Expert | Senior Consultant @ Capgemini Invent

Lecturer || Funded Investigator || Logistics, Supply Chain and Smart Manufacturing

Ceres Solver is an open source C++ library for modeling and solving large, complicated optimization problems. It can be used to solve Non-linear Least Squares problems with bounds constraints and general unconstrained optimization problems.

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.

Optimization Data Scientist at MaxAB, spreads the OR word through stories.

An Open-Source java library for constraint programming

Chuffed is a state of the art lazy clause solver designed from the ground up with lazy clause generation in mind.

http://clarabel.rs/ is a Rust implementation of an interior point numerical solver for convex optimization problems using a novel homogeneous embedding.

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?

An introduction to algorithms and computational complexity to solve combinatorial optimization problems

Operations research and computers interact in many scientific fields of vital importance to our society. These include, among others, transportation, economics, investment strategy, inventory control, logistics, safety, reliability, urban planning, and ecology. Computers & Operations Research (COR) provides an international forum for the application of computers and operations research techniques to problems in these and related fields.

Index with conferences about Operations Research for the following years

Index with conferences about Optimization for the following years

CONOPT is a feasible path solver based on advanced active set methods, particularly suited for large and sparse models.

A mathematical optimization solver for large-scale optimization problems. It is independently developed by Cardinal Operations, and it includes high-performance solvers for LP, MIP, SDP, (MI)SOCP, convex (MI)QP, convex (MI)QCP and exponential cone programming.

International conference about Constraint Programming

International conference about the integration of Constraint Programming, Artificial Intelligence and Operations Research

The IBM ILOG CPLEX Optimizer solves integer programming problems, very large[3] linear programming problems using either primal or dual variants of the simplex method or the barrier interior point method, convex and non-convex quadratic programming problems, and convex quadratically constrained problems (solved via second-order cone programming, or SOCP).

CSPLib is a library of test problems for constraint solvers.

Achieve world-record speed on large-scale problems with millions of constraints and variables—saving time and reducing costs.

A game to better understand how CVRP works.

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.

Community for Decision Management, including Machine Learning and Optimization

Challenges from the Center for Discrete Mathematics and Theoretical Computer Science

The CVXPY Discord community is a group of people who use the CVXPY software to solve convex optimization problems in Python

The HiGHS Discord server.

Discord community about Operations Research

Discord community about OR-Tools, a Google framework for mathematical modeling and solvers

Journal covering algorithmic and applied areas of discrete mathematics

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

Discrete Optimization Talks (DOTs) is a virtual seminar series from the Mixed Integer Programming Society (MIPS), a technical section of the Mathematical Optimization Society (MOS). Topics of interest are theoretical, computational, and applied aspects of integer and combinatorial optimization. The typical format of each session is two 30-minute talks.

Professor in Operations Research at Copenhagen Business School; Editor-in-Chief of TOP, the OR journal of SEIO.

EURO is the 'Association of European Operational Research Societies'. The objectives of EURO aim to promote Operational Research within Europe.

It is a peer-reviewed academic journal in operations research. It was founded in 1977 by the Association of European Operational Research Societies

Where Operations Research practitioners share real-world strategies and emerging techniques for optimal decision-making.

The FICO Xpress optimizer is a commercial optimization solver for linear programming (LP), mixed integer linear programming (MILP), convex quadratic programming (QP), convex quadratically constrained quadratic programming (QCQP), second-order cone programming (SOCP) and their mixed integer counterparts. Xpress includes a general purpose non-linear solver, Xpress NonLinear, including a successive linear programming algorithm (SLP, first-order method), and Artelys Knitro (second-order methods).

Blog with news from one of the biggest companies in the world optimizing chip making

Solve NP-hard optimization problems with Timefold AI.

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.

A selection of case studies that demonstrate the diverse application areas of mathematical optimization with GAMS.

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.

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.

Co-Founder + CTO at Timefold AI.

For solving large-scale linear programming (LP), mixed integer programming (MIP), and other related problems. It is a set of routines written in ANSI C and organized in the form of a callable library.

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

Gurobi Optimizer is a prescriptive analytics platform and a decision-making technology developed by Gurobi Optimization, LLC. The Gurobi Optimizer (often referred to as simply, “Gurobi”) is a solver, since it uses mathematical optimization to calculate the answer to a problem.

Blog with news from Gurobi, the company behind one of the most important solvers globally

Use cases from Gurobi

Insights from different case studies of companies using Gurobi

A gentle introduction to optimization with Python.

Heuristic-based solver with great results in complex problems

Success stories from different companies using Hexaly

HiGHS is open-source software to solve linear programming (LP), mixed-integer programming (MIP), and convex quadratic programming (QP) models.

To solve a sparse symmetric system of linear equations.

Huub is a Lazy Clause Generation (LCG) solver with a focus on modularity and maintainability in addition to speed. LCG solvers are a class of solvers that can be used to solve decision and optimization problems. They are characterized by their ability to dynamically add new Boolean variables and clauses to a Boolean Satisfiability (SAT) solver during the search process

International Conference on Operations Research and Enterprise Systems

The International Federation of Operational Research Societies (IFORS) is an umbrella organization for national operations research societies of over 45 countries

It features conversations between students, faculty and professionals around OR-related topics

Analytics, Data Science, and AI - Actionable insights and thoughts to drive positive business transformation and impact.

INFORMS is the leading international association for Operations Research & Analytics professionals.

Calendar of events from INFORMS

Optimization software that leverages machine learning to provide unparalleled performance.

One puzzle every week.

International Conference on Operations Research

It is a peer-reviewed academic journal which is published six times a year by Wiley-Blackwell on behalf of the International Federation of Operational Research Societies. The editorial mission of the journal is to advance the theory and practice of Operational Research and Management Science internationally

Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness.

An introduction to Operations Research with theory from Linear Programming to simulation, passing through Nonlinear Programming, Game Theory, Metaheuristics or Network flows, among others.

Ipopt (Interior Point Optimizer, pronounced "Eye-Pea-Opt") is an open source software package for large-scale nonlinear optimization. It can be used to solve general nonlinear programming problems

VP Product Strategy & Industry Solutions

Leveraging data in Logistics and Supply Chain Management | #datainlogistics | PhD in Machine Learning | Industrial Engineer

Optimization consultant at Decide4AI sharing impactful tips on coding for OR projects.

J.D. Kelly is an Advanced Planning and Scheduling (APS) and Advanced Process Control (APC) expert in the process industries including both optimization and estimation technologies otherwise known as Advanced Production-chain Control, Optimization and Estimation (APCOE)

jMetal is a Java-based framework for multi-objective optimization with metaheuristics.

Senior Data Scientist | Machine Learning Engineer | Decision Scientist | Optmization | Operations Research | Python | SQL | SAS

Reader in Mathematics at the University of Edinburgh

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

An innovative constraints programming component able to solve quickly and efficiently a wide range of combinatorial problems relying on an interactive and user-friendly hybrid framework including constraint programming, mixed-integer programming and artificial intelligence.

Sr Operations Research Analyst at Avista

Professor of Decision and Operation Technologies at Bielefeld University.

The most advanced solver for nonlinear optimization.

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.

Professor of Industrial and Systems Engineering at the University of Wisconsin-Madison, 2023 INFORMS President.

LGO is capable of determining high-quality solutions to global optimization problems that have (possibly many) locally optimal solutions. Because LGO makes only limited assumptions as to problem structure and differentiability, it can be applied in a broad range of design and operational applications.

LINGO includes a set of built-in solvers to tackle a wide variety of problems. Unlike many modeling packages, all of the LINGO solvers are directly linked to the modeling environment.

LOQO is a powerful solver for smooth constrained optimization problems, based on interior-point method applied to a sequence of quadratic approximations. Subject to the requirement that the defining functions be smooth (at the points evaluated by the algorithm), LOQO can handle a range of problems: linear or nonlinear, convex or nonconvex, constrained or unconstrained. For convex problems, LOQO finds a globally optimal solution; otherwise, it iterates from the given starting point to find a locally optimal solution.

A Mixed Integer Linear Programming (MILP) solver.

Professor of operations research at RWTH Aachen University.

It is a quarterly peer-reviewed scientific journal established in February 1976. It focuses on areas of mathematics relevant to the field of operations research such as continuous optimization, discrete optimization, game theory, machine learning, simulation methodology, and stochastic models. The journal is published by INFORMS (Institute for Operations Research and the Management Sciences)

A new interface for Google OR-Tools.

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

Assistant Professor of Transportation Engineering @ York University | Director of Interactive-OR | Amazon Visiting Academic @ Amazon

Creator of Optimization Solvers, CEO at InsideOpt.

International Conference on Metaheuristics and Nature Inspired Computing

Metaheuristics International Conference

Principal Research Scientist | AI Planning, Reasoning, and Decision-Making Systems; Executive Council Board Member at ICAPS and at AAAI, AAAI Senior Member

Teaching and writing about all things AI, operations, and his startup experience.

Practical AI for business, my experience starting and selling a company, and other content.

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

MINOS is an established choice for both linear and nonlinear optimization problems. It incorporates proven methods for large-scale sparse nonlinear constraints, and its methods are especially effective for nonlinear objectives subject to linear and near-linear constraints.

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.

Thought leadership from the MIT Center for Transportation & Logistics.

Introduction to the field of mathematical optimization.

A discussion about books focused on duality theory

Annual challenges from the University of Lehigh

Solves your LPs, QPs, SOCPs, SDPs, and MIPs. Includes interfaces to C, C++, Java, MATLAB, .NET, Python, Julia, Rust and R.

The Network consists of six academic and nine industrial participants from five EU countries, USA and Chile. The participants combine strong and complementary expertise, within industry sectors ranging from energy, retailing, insurance to banking, as well as national statistical offices.

A gradient-free optimization platform.

Roundup of Operations Research, Decision Science, and DecisionOps content from Nextmv and the optimization community

NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms.

Journal about Operations Research from INFORMS

It is a bimonthly peer-reviewed academic journal covering operations research. It was established in 1981

A book covering the basics of Operations Research

Blog with news about optimization of structures and processes (including logistics planning, network planning, production planning…)

Challenges with different optimization problems

Business Intelligence using optimal decision making tools.

This book offers an up-to-date description of relaxation/approximation and decomposition techniques, demonstrating how their combined use efficiently solves large-scale optimization problems relevant to engineering, particularly in electrical, and industrial engineering, with a focus on energy.

An interesting book about Column Generation to tackle large-scale optimization problems

Discussions around optimization, interviewing academics in the field of Operations Research and Industrial Engineering

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.

Customer success stories from ORTEC

Senior Data Scientist at Horvath who shares case studies and mini interviews.

The OSQP (Operator Splitting Quadratic Program) solver is a numerical optimization package for solving convex quadratic programs.

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

The PATH solver for MCP models is a Newton-based solver that combines a number of the most effective variations, extensions, and enhancements of this powerful technique.

PATHNLP is a solver for large nonlinear programming problems that builds on the PATH algorithm, extending it from mixed complementarity problems to general NLPs. PATHNLP is distributed through the GAMS ecosystem.

Manager, Operations Research & Data Science | Optimization Expert (Ph.D.)

Logistics Data Scientist + Founder of Open Door Logistics.

Planning education for real-world stuff, the newsletter for problem solvers at scale.

🌟 Welcome to the Prescriptive Analytics and Decision Optimization (PRADO) Series 2025! 🌟 The series of presentations about OR in practice, tools, and technologies. 📅 Program Sneak Peek: 🎤 March: Optimizing pharmacy procurement with substitution of drugs

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.

President of Optisol, Scheduling Specialist for High-Variety, Order-Driven Production and Resource-Constrained Projects.

An LP modeler written in Python

Laura Albert’s newsletter about OR.

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.

The podcast from INFORMS that talks about different topics around Operations Research

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.

SBB is a GAMS solver for Mixed Integer Nonlinear Programming (MINLP) models. It is based on a combination of the standard Branch and Bound (B&B) method known from Mixed Integer Linear Programming and some of the standard NLP solvers already supported by GAMS. SBB can use all GAMS NLP solvers as subsolvers but it works best with NLP solvers that can utilize a near optimal point as a starting point like Conopt, Minos, and Snopt.SBB supports all types of discrete variables supported by GAMS, including Binary, Integer, Semicont, Semiint, Sos1, and Sos2.

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.

SCS (Splitting Conic Solver) is a numerical optimization package for solving large-scale convex quadratic cone problems. The code is freely available on https://github.com/cvxgrp/scs. It solves primal-dual problems.

The Spanish Statistical and Operational Research Society is a Spanish organization that promotes the development and practice of statistics and operational research.

Annual challenges organized by Shell AI team.

SHOT (Supporting Hyperplane Optimization Toolkit) is a deterministic solver for mixed-integer nonlinear programming problems (MINLPs). Originally, SHOT was intended for convex MINLP problems only, but now also has functionality to solve nonconvex MINLP problems as a heuristic method without providing any guarantees of global optimality. SHOT can solve certain nonconvex problem types to global optimality as well.

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

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.

A software package for solving large-scale optimization problems (linear and nonlinear programs). It employs a sparse SQP algorithm with limited-memory quasi-Newton approximations to the Hessian of Lagrangian. SNOPT is especially effective for nonlinear problems whose functions and gradients are expensive to evaluate.

Blog about mathematical modeling with Python and Excel

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

Stack Exchange about Operations Research topics

OR Scientist at American Tire Distributors. OR, Python, Interviewing Content and More.

"Subject to" offers a series of informal conversations with relevant figures in the fields of Operations Research, Combinatorial Optimization and Logistics, and they are hosted by Anand Subramanian, an Associate Professor at Universidade Federal da Paraíba (UFPB), Brazil

Subreddit about Operations Research

Subreddit about Optimization

The Decision Intelligence Lab explores practical challenges of applying data science, analytics, and AI to drive real-world business outcomes. Hosted by Prof. Michael Watson (Nortwestern University) and Prof. Vijay Mehrotra (University of San Francisco) - both seasoned entrepreneurs, consultants, and researchers - this podcast delivers real-world insights for data professionals, business leaders, & anyone seeking to leverage data for smarter decision making. Each episode features leaders sharing how smarter decisions are reshaping business and technology.

Advice from a decision strategist with 19 years expertise in analytics & AI, inc. Gartner, system integrators & industry

The Operational Research Society (ORS), also known as The OR Society, is an international learned society in the field of operational research (OR), with more than 3,100 members

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

Self-employed OR Engineer at Bluebird Optimization sharing insights about the impact of optimization in businesses.

Updated fork from OptaPlanner

Mathematical Optimization Researcher, Teacher, and Manager

Another game with map visualizations for the TSP.

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

Uno (Unifying Nonlinear Optimization) is a C++ library that unifies methods for solving nonlinearly constrained optimization problems.

Vehicle Routing and Logistics work group from EURO

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…

Professor Emeritus, Princeton University/ Co-Founder, Optimal Dynamics, shares knowledge about sequential decision problems.

Senior Decision Scientist at Aimpoint Digital | Decision Sciences, Mathematical Modeling

X (Twitter) list with accounts related to Operations Research

Z3 is a theorem prover from Microsoft Research.

Consultant: Solving the Meta-Problem focused on Data and Supply Chains | Data Analytics, Inventory, Lean Warehouse, Process Improvement