Warren Ochibobo
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JuMP and MathOptInterface.jl give access to many solvers, both very common in the industry and more specialised. Google offers its own in-house solvers as part of the open-source package OR-Tools: Glop, a simplex solver; CP-SAT, an award-winning constraint-programming solver; PDLP, a first-order solver for large-scale linear programming.
ORTools.jl is a recent package that gives access to these solvers through MathOptInterface.jl. It supports both local and remote use, meaning that users do not need a local installation to solve linear and integer problems thanks to Google Cloud. More recently, ORTools.jl started offering a native interface for constraint programming building upon the work in MathOptInterface.jl.
However, OR-Tools have more than this to offer, including a scalable routing solver for large-scale VRPs or state-of-the-art set-cover solver. MathOptInterface.jl does not yet propose an interface for these problems and we would like to gauge the community’s interest in these specific solvers.
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Preview abstract
Google has a long tradition of open-source software, which encompasses the field of operations research with OR-Tools. In development since 2008, it offers several solvers useful to many OR practitioners:
- PDLP, a revolutionary first-order linear solver that is reshaping the landscape of linear optimisation;
- CP-SAT, an award-winning constraint-programming solver;
- Glop, an accurate linear solver;
- Routing, a vehicle routing solver underpinning Google Maps Platform Route Optimization.
OR-Tools has long had its features accessible from other languages: the core algorithms are implemented in C++ for performance, but users can tap into them in Python, Java, C#, or Go.
It is recently available in Julia too, with a current focus on the linear and constraint solvers, either locally or remotely.
We provide a wrapper for our solvers that brings them to JuMP.jl through MathOptInterface.jl.
This tutorial will walk you through the features of OR-Tools and its solvers, then show examples of using OR-Tools from within Julia, either through JuMP or a lower-level interface.
We will also share our experience of C++-Julia interop.
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Preview abstract
Google has a long tradition of open-source software, which encompasses the field of operations research with OR-Tools. In development since 2008, it offers several solvers useful to many OR practitioners:
- PDLP, a revolutionary first-order linear solver that is reshaping the landscape of linear optimisation;
- CP-SAT, an award-winning constraint-programming solver;
- Glop, an accurate linear solver;
- Routing, a vehicle routing solver underpinning Google Maps Platform Route Optimization.
OR-Tools has long had its features accessible from other languages: the core algorithms are implemented in C++ for performance, but users can tap into them in Python, Java, C#, or Go.
It is recently available in Julia too, with a current focus on the linear and constraint solvers, either locally or remotely.
We provide a wrapper for our solvers that brings them to JuMP.jl through MathOptInterface.jl.
This tutorial will walk you through the features of OR-Tools and its solvers, then show examples of using OR-Tools from within Julia, either through JuMP or a lower-level interface.
We will also share our experience of C++-Julia interop.
View details
Preview abstract
In Julia, JuMP is the go-to modelling package for mathematical optimisation. As of this writing, Google's award-winning solvers have not been accessible through JuMP; which offers Julia's ease of use. ORTools.jl is changing this. Julia users will now have access to Google's Glop, CP-SAT, and PDLP solvers through JuMP as provided by the ORTools.jl package.
This talk offers an introduction to the features of the package and an overview of the difficulties we encountered.
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