# The SCIP Optimization Suite 10.0

arXiv: https://arxiv.org/abs/2511.18580 · HTML: https://mlsanity.com/paper/2511.18580/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Nov 2025.

## Built on by (most cited first, 4 of 4)

- [Optimal Software Pipelining and Warp Specialization for Tensor Core GPUs](https://mlsanity.com/paper/2512.18134/) (2025)
- [Agentic MIP Research: Accelerated Constraint Handler Generation](https://mlsanity.com/paper/2605.09186/) (2026)
- [On inferring cumulative constraints](https://mlsanity.com/paper/2602.15635/) (2026)
- [Accelerated Relax-and-Round for Concave Coverage Problems](https://mlsanity.com/paper/2605.06900/) (2026)

## Abstract (arXiv)

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization, centered around the constraint integer programming (CIP) framework SCIP. This report discusses the enhancements and extensions included in SCIP Optimization Suite 10.0. The updates in SCIP 10.0 include a new solving mode for exactly solving rational mixed-integer linear programs, a new presolver for detecting implied integral variables, a novel cut-based conflict analysis and separator for flower inequalities, two new heuristics, a novel tool for explaining infeasibility, a new interface for nonlinear solvers as well as improvements in symmetry handling, branching strategies, and SCIP's Benders' decomposition framework. SCIP Optimization Suite 10.0 also includes new and improved features in the the presolving library PaPILO, the parallel framework UG, and the decomposition framework GCG. Moreover, the SCIP Optimization Suite 10.0 contains MIP-DD, the first open-source delta debugger for mixed-integer programming solvers. These additions and enhancements have resulted in an overall performance improvement of SCIP in terms of solving time, number of nodes in the branch-and-bound tree, as well as the reliability of the solver.