A safe Rust interface for SCIP. This crate also exposes access to the
SCIP's C-API through the ffi module.
The project is currently actively developed, issues/pull-requests are very welcome.
The easiest way is to run this in your crate directory
cargo add russcip --features bundledfor other installation methods, please check INSTALL.md.
An example on how to model and solve an integer program can be found in the examples directory.
The ffi module provides access to the raw C-API of SCIP. This can be used to call functions that are not wrapped in
the safe interface yet.
The scip_ptr unsafe function in the Model struct, which gives you access to the underlying SCIP raw pointer.
Each other wrapper struct has a similar function named inner, e.g. Variable::inner or Constraint::inner gives you
a *mut ffi::SCIP_VAR or *mut ffi::SCIP_CONS respectively.
Some of SCIP's plugins are imported to the rust interface as traits. Currently the implemented plugins are:
| Name | File | Docs |
|---|---|---|
| Branching rule | branchrule.rs | docs |
| Variable Pricer | pricer.rs | docs |
| Event Handler | eventhdlr.rs | docs |
| Primal Heuristic | heuristic.rs | docs |
| Separator | separator.rs | docs |
To add a custom plugin to a SCIP Model instance, you should implement its trait and call the corresponding
include_{PLUGIN_NAME} method. For examples on implementing the specific plugin trait you can check the tests in the
corresponding files.
Thinking about contributing to russcip? First of all thank you! You can check our issues page, there's a bunch of good_first_issues, or you can check our contribution guide. If you'd like to contribute and unsure what to do, or thinking about a big feature and want to discuss if it makes sense and what is the best way to do it? you could open a new issue/discussion or send me a quick email @mmghannam.
SCIP is currently one of the fastest non-commercial solvers for mixed integer programming (MIP) and mixed integer nonlinear programming (MINLP). It is also a framework for constraint integer programming and branch-cut-and-price. It allows for total control of the solution process and the access of detailed information down to the guts of the solver.