Find your next solver

Decision Science Leader at Toyota sharing career development tips.

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

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

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

Sales at Gurobi, shares interesting posts about Gurobi.

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

Optimization Expert | Algorithm Design | Operations Research

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.

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

PhD Operations Research | Lead Engineer @ FICO

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.

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

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

CSPLib is a library of test problems for constraint solvers.

A game to better understand how CVRP works.

Instances for the CVRP challenge.

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

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

Co-Founder + CTO at Timefold AI.

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)

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

Reader in Mathematics at the University of Edinburgh

Sr Operations Research Analyst at Avista

Professor of Decision and Operation Technologies at Bielefeld University.

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

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.

Professor of operations research at RWTH Aachen University.

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.

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.

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.

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.

Instances for several interesting NP-hard problems.

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

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

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

Logistics Data Scientist + Founder of Open Door Logistics.

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).

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

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

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.

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

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

Learn about cutting planes in an adictive way.

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

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.

Mathematical Optimization Researcher, Teacher, and Manager

Another game with map visualizations for the TSP.

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

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…

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

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

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