Find your next solver
A curated index of Operations Research resources — solvers, courses, books, datasets, communities and more. Classified by type, topic and audience.
17 resources matching
- Advanced modeling for discrete optimizationCourse
Course about advanced modeling for discrete optimization, covering topics such as debugging or predicates
- AIMMS use casesUse cases
Case studies from AIMMS
- Amazon ScienceBlog
Blog with news from the Operations Research and Optimization group at Amazon
- AMPL use casesUse cases
Optimization problems in businesses using AMPL
- 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
- GAMS use casesUse cases
A selection of case studies that demonstrate the diverse application areas of mathematical optimization with GAMS.
- Gurobi blogBlog
Blog with news from Gurobi, the company behind one of the most important solvers globally
- Gurobi case studiesBlog
Use cases from Gurobi
- Gurobi use casesUse cases
Insights from different case studies of companies using Gurobi
- Hexaly use casesUse cases
Success stories from different companies using Hexaly
- Optano blogBlog
Blog with news about optimization of structures and processes (including logistics planning, network planning, production planning…)
- ORTECUse cases
Customer success stories from ORTEC
- 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.
- Solvermax blogBlog
Blog about mathematical modeling with Python and Excel
- Solving algorithms for discrete optimizationCourse
Course about solving discrete optimization problems with different techniques: Constraint Programming, Mixed Integer Programming and Local Search