# Enabling Research through the SCIP Optimization Suite 8.0

arXiv: https://arxiv.org/abs/2303.07101 · HTML: https://mlsanity.com/paper/2303.07101/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Mar 2023.

## Built on by (most cited first, 14 of 14)

- [Verifying message-passing neural networks via topology-based bounds tightening](https://mlsanity.com/paper/2402.13937/) (2024)
- [PySCIPOpt-ML: Embedding Trained Machine Learning Models into Mixed-Integer Programs](https://mlsanity.com/paper/2312.08074/) (2023)
- [Effective Generation of Feasible Solutions for Integer Programming via Guided Diffusion](https://mlsanity.com/paper/2406.12349/) (2024)
- [Learning to Remove Cuts in Integer Linear Programming](https://mlsanity.com/paper/2406.18781/) (2024)
- [Graph-SCP: Accelerating Set Cover Problems with Graph Neural Networks](https://mlsanity.com/paper/2310.07979/) (2023)
- [Formally Verified Approximate Policy Iteration](https://mlsanity.com/paper/2406.07340/) (2024)
- [An information-matching approach to optimal experimental design and active learning](https://mlsanity.com/paper/2411.02740/) (2024)
- [A Context-Aware Cutting Plane Selection Algorithm for Mixed-Integer Programming](https://mlsanity.com/paper/2307.07322/) (2023)
- [A Penalty-Based Guardrail Algorithm for Non-Decreasing Optimization with Inequality Constraints](https://mlsanity.com/paper/2405.01984/) (2024)
- [Asteroid Mining: ACT&Friends' Results for the GTOC 12 Problem](https://mlsanity.com/paper/2410.20839/) (2024)
- [Similarity-based fuzzy clustering scientific articles: potentials and challenges from mathematical and computational perspectives](https://mlsanity.com/paper/2506.04045/) (2025)
- [Robustness Verification of Graph Neural Networks Via Lightweight Satisfiability Testing](https://mlsanity.com/paper/2510.18591/) (2025)
- [Distribution-Aware Algorithm Design with LLM Agents](https://mlsanity.com/paper/2605.14141/) (2026)
- [When Solvers Get Moody: Quantifying and Predicting Performance Variability in Mixed Integer Programming](https://mlsanity.com/paper/2610.12876/) (2026)

## Abstract (arXiv)

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. The focus of this paper is on the role of the SCIP Optimization Suite in supporting research. SCIP's main design principles are discussed, followed by a presentation of the latest performance improvements and developments in version 8.0, which serve both as examples of SCIP's application as a research tool and as a platform for further developments. Further, the paper gives an overview of interfaces to other programming and modeling languages, new features that expand the possibilities for user interaction with the framework, and the latest developments in several extensions built upon SCIP.