# ACE, a generic constraint solver

arXiv: https://arxiv.org/abs/2302.05405 · HTML: https://mlsanity.com/paper/2302.05405/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 37 references that are in the map.
- First posted on arXiv 6 Jan 2023.

## Builds on (most cited first, 5 of 5)

- [PyCSP3: Modeling Combinatorial Constrained Problems in Python](https://mlsanity.com/paper/2009.00326/) (2020)
- [XCSP3: An Integrated Format for Benchmarking Combinatorial Constrained Problems](https://mlsanity.com/paper/1611.03398/) (2016)
- [XCSP3-core: A Format for Representing Constraint Satisfaction/Optimization Problems](https://mlsanity.com/paper/2009.00514/) (2020)
- [Compact-Table: Efficiently Filtering Table Constraints with Reversible Sparse Bit-Sets](https://mlsanity.com/paper/1604.06641/) (2016)
- [Proceedings of the 2022 XCSP3 Competition](https://mlsanity.com/paper/2209.00917/) (2022)

## Built on by (most cited first, 3 of 3)

- [Proceedings of the 2023 XCSP3 Competition](https://mlsanity.com/paper/2312.05877/) (2023)
- [Hyperparameter Optimization of Constraint Programming Solvers](https://mlsanity.com/paper/2601.11389/) (2026)
- [PyCSP3-Scheduling: A Scheduling Extension for PyCSP3](https://mlsanity.com/paper/2605.14559/) (2026)

## Abstract (arXiv)

Constraint Programming (CP) is a useful technology for modeling and solving combinatorial constrained problems. On the one hand, on can use a library like PyCSP3 for easily modeling problems arising in various application fields (e.g., scheduling, planning, data-mining, cryptography, bio-informatics, organic chemistry, etc.). Problem instances can then be directly generated from specific models and data. On the other hand, for solving instances (notably, represented in XCSP3 format), one can use a constraint solver like ACE, which is presented in this paper. ACE is an open-source constraint solver, developed in Java, which focuses on integer variables (including 0/1-Boolean variables), state-of-the-art table constraints, popular global constraints, search heuristics and (mono-criterion) optimization.