Find your next solver
A curated index of Operations Research resources — solvers, courses, books, datasets, communities and more. Classified by type, topic and audience.
20 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
- Discrete Optimization courseCourse
Course about discrete optimization covering a wide range of optimization techniques such as Constraint Programming, Local Search or Column Generation
- Flexciton newsBlog
Blog with news from one of the biggest companies in the world optimizing chip making
- Free the world from wasteful scheduling with Timefold AIVideo
Solve NP-hard optimization problems with Timefold AI.
- Geoffrey De SmetContent creator
Co-Founder + CTO at Timefold AI.
- Jeffrey Dean KellyContent creator
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)
- 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.
- 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.
- PlannedNewsletter
Planning education for real-world stuff, the newsletter for problem solvers at scale.
- Solving algorithms for discrete optimizationCourse
Course about solving discrete optimization problems with different techniques: Constraint Programming, Mixed Integer Programming and Local Search
- Timefold use casesUse cases
Customer stories of companies using Timefold for planning problems
- 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).