Find your next solver
A curated index of Operations Research resources — solvers, courses, books, datasets, communities and more. Classified by type, topic and audience.
22 resources matching
- Advanced modeling for discrete optimizationCourse
Course about advanced modeling for discrete optimization, covering topics such as debugging or predicates
- AliGorithmVideo
YouTube channel with interesting knowledge about optimization.
- Anything you can do I can do betterVideo
Prof Marco Lubbecke talks about optimization in a TED Talk.
- Basic modeling for discrete optimizationCourse
Course about basic modeling for discrete optimization with MiniZinc
- Conference index Operations ResearchConference
Index with conferences about Operations Research for the following years
- Conference index OptimizationConference
Index with conferences about Optimization for the following years
- CP ConferenceConference
International conference about Constraint Programming
- CPAIORConference
International conference about the integration of Constraint Programming, Artificial Intelligence and Operations Research
- Discrete Optimization courseCourse
Course about discrete optimization covering a wide range of optimization techniques such as Constraint Programming, Local Search or Column Generation
- Free the world from wasteful scheduling with Timefold AIVideo
Solve NP-hard optimization problems with Timefold AI.
- ICORESConference
International Conference on Operations Research and Enterprise Systems
- INFORMS Calendar of eventsConference
Calendar of events from INFORMS
- International Conference on Operations Research (OR)Conference
International Conference on Operations Research
- MathOpt: Solver Independent Modeling in Google OR-ToolsVideo
A new interface for Google OR-Tools.
- Metaheuristics and Nature Inspired Computing Conference 2023Conference
International Conference on Metaheuristics and Nature Inspired Computing
- Metaheuristics International Conference (MIC)Conference
Metaheuristics International Conference
- 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.
- OR from 0 to 1Course
7-day free email course to kickstart in Operations Research.
- Pragmatic OR: Solving large scale optimization problems in fast moving environmentsVideo
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.
- RWTHx: Mathematical Optimization for EngineersCourse
Course about all things mathematical optimization: unconstrained, LP, NLP, MIP, Global optimization, Dynamic optimization, ML for optimization, and optimization under uncertainty.
- Solving algorithms for discrete optimizationCourse
Course about solving discrete optimization problems with different techniques: Constraint Programming, Mixed Integer Programming and Local Search