Find your next solver

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

Learn supply chain principles through a visual simulation.

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.

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

A game to better understand how CVRP works.

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

A gentle introduction to optimization with Python.

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.

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.

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.

A discussion about books focused on duality theory

A book covering the basics of Operations Research

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.

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

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).

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

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

Stack Exchange about Operations Research topics

Subreddit about Operations Research

Subreddit about Optimization

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).

X (Twitter) list with accounts related to Operations Research