Specifications PyCSP3 Tools Instances Competitions About

XCSP3

XCSP3 is an XML-based format designed to represent instances of combinatorial constrained problems from the angle of Constraint Programming (CP). XCSP3 is an intermediate integrated format that can represent each instance separately while preserving its structure. Important:

  • for only dealing with the most popular constraints and frameworks, use XCSP3-core;
  • for modeling problems declaratively, and compiling them into XCSP3 instances, use the Python library PyCSP3.
Licence: Creative commons (CC BY-SA 4.0) for specifications and MIT Licence for any derived piece of software and benchmarks

Constraint Programming Format

XCSP3 allows you to deal with:
- Decision Problems encoded as CSP (Constraint Satisfaction Problem)
- Optimization Problems encoded as COP (Constrained Optimization Problem)


Comprehensive Format

Many supported frameworks: CSP, COP, WCSP, QCSP, DisCSP, ...
Many types of variables and constraints
Many variations of popular constraints
Reification and Relaxation
Annotations

Structure-Preserving Format

Natural mechanisms to keep structure:
- Arrays of variables
- Groups of constraints
- Blocks of constraints
- Meta-constraints

Resources and Tools

Well-documented specifications
Parsers developped in Java, C++, Rust and Python
PyCSP3: Python Library for modeling
More than 23,000 instances

Last News

September 5, 2024
Results of the 2024 XCSP3 Competition (at CP'24).
August 28, 2024
Specifications 3.2 of XCSP3. Version 2.4 of PyCSP3.
December 10, 2023
PySCP3 2.2 , Version 2.2 of the Python library PyCSP3.
August 30, 2023
Results of the 2023 XCSP3 Competition; held with CP 2023.
August 3, 2022
Results of the 2022 XCSP3 Competition, held with FLoC 2022 (Olympic Games).

Here, we present two XCSP3 instances for two well-known problems:

Knapsack problem

<instance format="XCSP3" type="COP">
  <variables>
    <array id="x" size="[5]"> 0 1 </array>
  </variables>
  <constraints>
    <sum>
      <list> x[] </list>
      <coeffs> 11 24 5 23 16 </coeffs>
      <condition> (le,100) </condition>
    </sum>
  </constraints>
  <objectives>
    <maximize type="sum">
      <list> x[] </list>
      <coeffs> 46 46 38 88 3 </coeffs>
    </maximize>
  </objectives>
 </instance>

All Interval problem

<instance format="XCSP3" type="CSP">
  <variables>
    <array id="x" size="[5]" note="x[i] is the ith value of the series">
      0..4
    </array>
    <array id="y" size="[4]" note="y[i] is the distance between x[i] and x[i+1]">
      1..4
    </array>
  </variables>
  <constraints>
    <allDifferent> x[] </allDifferent>
    <allDifferent> y[] </allDifferent>
    <group class="channeling">
      <intension> eq(%0,dist(%1,%2)) </intension>
      <args> y[0] x[0] x[1] </args>
      <args> y[1] x[1] x[2] </args>
      <args> y[2] x[2] x[3] </args>
      <args> y[3] x[3] x[4] </args>
    </group>
  </constraints>
</instance>

Some Features

 Specifications

  • Download the full documentation of XCSP3
  • Download the documentation of XCSP3-core

 Series of Instances

This website contains many series of XCSP3 problem instances.

 Tools

  • A Java 8 Parser, a C++ 11 Parser, a Rust and a Python parser are available
  • A Java 8 Solution Checker is available

 Modeling

  • A Python Library for modeling and compiling problems: PyCSP3

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