4 releases (2 breaking)
0.3.1 | Aug 7, 2024 |
---|---|
0.3.0 | Feb 23, 2024 |
0.2.0 | Sep 5, 2023 |
0.1.0 | Jul 12, 2023 |
#543 in Math
1MB
6.5K
SLoC
Scuttle - A Multi-Objective MaxSAT Solver in Rust
Scuttle is a multi-objective MaxSAT solver written in Rust and based on the RustSAT library and the CaDiCaL SAT solver.
Publications
This solver was used in our CP'23 paper on preprocessing for multi-objective
optimization [5] and our CPAIOR'24 paper on core boosting [6].
Additional material for the CP'23 paper can be found
here while material for the
CPAIOR'24 paper is available in the cpaior24/
directory in this repository.
Algorithms
First argument | Description |
---|---|
p-minimal |
P-Minimal model enumeration as described in [1] and [2] |
lower-bounding |
Lower-bounding search as described in [3] (called "core-guiding" there) |
bioptsat |
Sat-Unsat variant of the BiOptSat algorithm described in [4] |
Building
If you simply want a binary of the solver, you can install it from
crates.io by running cargo install scuttle --locked
.
To build the project from source, you will need to clone RustSAT and MaxPre-rs within the same workspace directory as this repository.
workspace/
├── maxpre-rs/
├── rustsat/
└── scuttle/
You can then build scuttle
by running cargo build
within workspace/scuttle/
.
What's The Name
Apparently "scuttle" is one of multiple term for a group of crabs, which seemed fitting for a multi-objective solver in Rust.
References
- Takehide Soh and Mutsunori Banbara and Naoyuki Tamura and Daniel Le Berre: Solving Multiobjective Discrete Optimization Problems with Propositional Minimal Model Generation, CP 2017.
- Miyuki Koshimura and Hidetomo Nabeshima and Hiroshi Fujita and Ryuzo Hasegawa: Minimal Model Generation with Respect to an Atom Set, FTP 2009.
- Joao Cortes and Ines Lynce and Vasco M. Maquinho: New Core-Guided and Hitting Set Algorithms for Multi-Objective Combinatorial Optimization, TACAS 2023.
- Christoph Jabs and Jeremias Berg and Andreas Niskanen and Matti Järvisalo: MaxSAT-Based Bi-Objective Boolean Optimization, SAT 2022.
- Christoph Jabs and Jeremias Berg and Hannes Ihalainen and Matti Järvisalo: Preprocessing in SAT-Based Multi-Objective Combinatorial Optimization, CP 2023.
- Christoph Jabs and Jeremias Berg and Matti Järvisalo: Core Boosting in SAT-Based Multi-Objective Optimization, CPAIOR 2024.
Dependencies
~6–18MB
~200K SLoC