toulbar2
Exact optimization for cost function networks and additive graphical models
What is toulbar2?
toulbar2 is an open-source black-box C++ optimizer for cost function networks and discrete additive graphical models. This also covers Max-SAT, Max-Cut, QUBO (and constrained variants), among others. It can read a variety of formats. The optimized criteria and feasibility should be provided factorized in local cost functions on discrete variables. Constraints are represented as functions that produce costs that exceed a user-provided primal bound. toulbar2 looks for a non-forbidden assignment of all variables that optimizes the sum of all functions (a decision NP-complete problem).
toulbar2 won several competitions on deterministic and probabilistic graphical models:
- Max-CSP 2008 Competition CPAI08 (winner on 2-ARY-EXT and N-ARY-EXT)
- Probabilistic Inference Evaluation UAI 2008 (winner on several MPE tasks, inra entries)
- 2010 UAI APPROXIMATE INFERENCE CHALLENGE UAI 2010 (winner on 1200-second MPE task)
- The Probabilistic Inference Challenge PIC 2011 (second place by ficolofo on 1-hour MAP task)
- UAI 2014 Inference Competition UAI 2014 (winner on all MAP task categories, see Proteus, Robin, and IncTb entries)
- XCSP3 Competitions (first place on Mini COP in 2023 and 2025, second place on Mini COP and Parallel COP tracks in 2022, third place in 2024)
- UAI 2022 Inference Competition UAI 2022 (winner on all MPE and MMAP task categories)
- Pseudo-Boolean Competition 2025 PB25 (OPT-LIN ranking 39/46 ; PARTIAL-LIN ranking 6/9, but it gave the best known answer from an incomplete solver point of view in 185 instances among 208)
toulbar2 is now also able to collaborate with ML code that can learn an additive graphical model (with constraints) from data (see the associated paper, slides and video where it is shown how it can learn user preferences or how to play the Sudoku without knowing the rules). The current CFN learning code is available on GitHub.
Installation from binaries
You can install toulbar2 directly using the package manager in Debian and Debian derived Linux distributions (Ubuntu, Mint,...):
sudo apt-get update
sudo apt-get install toulbar2 toulbar2-doc
For the most recent binary or the Python API, compile from source.
Python interface pytoulbar2
pytoulbar2, the toulbar2 Python interface, can be installed using pip on Linux and MacOS (preferably in a virtual or conda environment):
python3 -m pip install --upgrade pip
python3 -m pip install pytoulbar2
The first line is only useful for Linux distributions that ship "old" versions of pip.
pytoulbar2 compilation (advanced)
The pytoulbar2 package can be compiled from toulbar2 sources with the pybind11 module.
- pybind11 can be installed globally:
sudo apt install pybind11-dev
- or in a virtual environment (recommended):
python3 -m venv ./pybind11_env
source ./pybind11_env/bin/activate
pip install pybind11[global]
⚠️ On Ubuntu, it might be necessary to install python development and virtual environment packages python3-dev and python3.12-venv.
Then, pytoulbar2 binaries can be compiled with cmake: cmake .. -DPYTB2=ON && cmake --build ..
Finally, add your toulbar2_build_path to the PYTHONPATH env variable: export PYTHONPATH=your_tb2_path/build and the pytoulbar2 interface should be operational.
Download
Download the latest release from GitHub (https://github.com/toulbar2/toulbar2) or similarly use tag versions, e.g.:
git clone --branch 1.2.2 https://github.com/toulbar2/toulbar2.git
Installation from sources
Compilation requires git, cmake and a C++-17 capable compiler (in C++17 mode).
Required library:
- libgmp-dev
- bc (used during cmake)
Recommended libraries (default use):
- libboost-graph-dev
- libboost-iostreams-dev
- libboost-serialization-dev
- zlib1g-dev
- liblzma-dev
- libbz2-dev
Optional libraries:
- libjemalloc-dev
- pybind11-dev
- libopenmpi-dev
- libboost-mpi-dev
- libicuuc
- libicui18n
- libicudata
- libxml2-dev
- libxcsp3parser
- libeigen3-dev
On MacOS, run ./misc/script/MacOS-requirements-install.sh to install the recommended libraries. For Mac with ARM64, add option -DBoost=OFF to cmake.
Commands for compiling toulbar2 on Linux/MacOS with cmake (binary in build/bin/*/toulbar2):
mkdir build
cd build
cmake ..
make
Commands for statically compiling toulbar2 on Linux in directory toulbar2/src without cmake:
bash
cd src
echo '#define Toulbar_VERSION "1.2.2"' > ToulbarVersion.hpp
echo -n "" > tb2config.hpp
g++ -o toulbar2 -std=c++17 -O3 -DNDEBUG -march=native -flto -static -static-libgcc -static-libstdc++ -DBOOST -DLONGDOUBLE_PROB -DLONGLONG_COST -DWCSPFORMATONLY \
-I. -I./pils/src tb2*.cpp applis/*.cpp convex/*.cpp core/*.cpp globals/*.cpp incop/*.cpp mcriteria/*.cpp pils/src/exe/*.cpp search/*.cpp utils/*.cpp vns/*.cpp ToulbarVersion.cpp \
-lboost_graph -lboost_iostreams -lboost_serialization -lgmp -lz -lbz2 -llzma
Use OPENMPI flag and MPI compiler for a parallel version of toulbar2 (must be run with mpirun, use mpirun -n 1 for the sequential version of HBFS or VNS):
bash
cd src
echo '#define Toulbar_VERSION "1.2.2"' > ToulbarVersion.hpp
echo -n "" > tb2config.hpp
mpicxx -o toulbar2 -std=c++17 -O3 -DNDEBUG -march=native -flto -DBOOST -DLONGDOUBLE_PROB -DLONGLONG_COST -DWCSPFORMATONLY -DOPENMPI \
-I. -I./pils/src tb2*.cpp applis/*.cpp convex/*.cpp core/*.cpp globals/*.cpp incop/*.cpp mcriteria/*.cpp pils/src/exe/*.cpp search/*.cpp utils/*.cpp vns/*.cpp ToulbarVersion.cpp \
-lboost_graph -lboost_iostreams -lboost_serialization -lboost_mpi -lgmp -lz -lbz2 -llzma
Replace LONGLONG_COST by INT_COST to reduce memory usage by two and reduced cost range (costs must be smaller than 10^8).
Replace WCSPFORMATONLY by XMLFLAG3 and add libxcsp3parser.a from xcsp.org in your current directory for reading XCSP3 files:
bash
cd src
echo '#define Toulbar_VERSION "1.2.2"' > ToulbarVersion.hpp
echo -n "" > tb2config.hpp
mpicxx -o toulbar2 -std=c++17 -O3 -DNDEBUG -march=native -flto -DBOOST -DLONGDOUBLE_PROB -DLONGLONG_COST -DXMLFLAG3 -DOPENMPI \
-I/usr/include/libxml2 -I. -I./pils/src -I./xmlcsp3 tb2*.cpp applis/*.cpp convex/*.cpp core/*.cpp globals/*.cpp incop/*.cpp mcriteria/*.cpp pils/src/exe/*.cpp search/*.cpp utils/*.cpp vns/*.cpp ToulbarVersion.cpp \
-lboost_graph -lboost_iostreams -lboost_serialization -lboost_mpi -lxml2 -licuuc -licui18n -licudata libxcsp3parser.a -lgmp -lz -lbz2 -llzma -lm -lpthread -ldl
Copyright (C) 2006-2026, toulbar2 team. toulbar2 is currently maintained by Simon de Givry, INRAE - MIAT, Toulouse, France (simon.de-givry@inrae.fr)
Release files for pytoulbar2 1.4.0.1
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