Find your next solver
A curated index of Operations Research resources — solvers, courses, books, datasets, communities and more. Classified by type, topic and audience.
19 resources matching
- Advanced modeling for discrete optimizationCourse
Course about advanced modeling for discrete optimization, covering topics such as debugging or predicates
- AI for Better PlanningNewsletter
Learn more about how AI is changing businesses and how you can leverage it: Insights, tools, tips, and expert voices
- Amazon ScienceBlog
Blog with news from the Operations Research and Optimization group at Amazon
- Anything you can do I can do betterVideo
Prof Marco Lubbecke talks about optimization in a TED Talk.
- ArcadeTSPGame
An arcade-style TSP challenge game written for https://github.com/tunnuz/arcadetsp's 2018 Christmas Party, follow the in-game instructions.
- Basic modeling for discrete optimizationCourse
Course about basic modeling for discrete optimization with MiniZinc
- Choco solverSolver
An Open-Source java library for constraint programming
- Discrete Optimization courseCourse
Course about discrete optimization covering a wide range of optimization techniques such as Constraint Programming, Local Search or Column Generation
- GecodeSolver
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.
- KalisSolver
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.
- Learn Graph TheoryGame
Interactive resources to learn Graph Theory.
- Mike Talks AINewsletter
Practical AI for business, my experience starting and selling a company, and other content.
- MiniZincModeling language
MiniZinc is a high-level constraint modelling language that allows you to easily express and solve discrete optimisation problems.
- MIPLearnSoftware
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.
- ML ain’t your only hammerVideo
Introduction to the field of mathematical optimization.
- Solving algorithms for discrete optimizationCourse
Course about solving discrete optimization problems with different techniques: Constraint Programming, Mixed Integer Programming and Local Search
- Timefold AISolver
Updated fork from OptaPlanner
- TSP ChallengeGame
Another game with map visualizations for the TSP.
- TSP GameGame
Solve the TSP in a visual way from the Productions and Operations Management (Universitat Wein).