An inference technique that is orthogonal to traditional methods like linear programming or constraint propagation is the detection of symmetric parts of the search space in order to avoid redundant work. Symmetry breaking is essential for the solution of symmetric combinatorial problems. However, the existing methods to handle symmetries in constraint programs require deep understanding and skill from the user. Consequently, in Cornflower we aim to provide algorithms that can break automatically detectable symmetries, thus making symmetry breaking part of the problem solution even for users who are not aware of symmetries at all.

Related Publications

• Pierre Flener, Justin Pearson, Meinolf Sellmann
  Static and Dynamic Structural Symmetry Breaking
  AMAI. To appear. 2009.


• Pierre Flener, Justin Pearson, Meinolf Sellmann, Pascal Van Hentenryck, Magnus Agren
  Dynamic Structural Symmetry Breaking for Constraint Satisfaction Problems
  Constraints. To appear.


• Daniel Heller, Aurojit Panda, Meinolf Sellmann, Justin Yip
  Model Restarts for Structural Symmetry Breaking
  Proceedings of the 14th intern. Conference on the Principles and Practice of Constraint Programming (CP), in print, 2008.


• Daniel Heller and Meinolf Sellmann
  Dynamic Symmetry Breaking Restarted
  Proceedings of the 12th intern. Conference on the Principles and Practice of Constraint Programming (CP), Springer LNCS 4204, pp. 721-725, 2006.


• Pierre Flener, Justin Pearson, Meinolf Sellmann, Pascal Van Hentenryck
  Static and Dynamic Structural Symmetry Breaking
  Proceedings of the 12th intern. Conference on the Principles and Practice of Constraint Programming (CP), Springer LNCS 4204, pp. 695-699, 2006.


• Meinolf Sellmann and Pascal Van Hentenryck
  Structural Symmetry Breaking
  Nineteenth International Joint Conference on Artificial Intelligence (IJCAI), 2005.