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Abstract

We present two constraints that partition the vertices of an undirected n-vertex, m-edge graph \({\mathcal{G}}=({\mathcal{V}},{\mathcal{E}})\) into a set of vertex-disjoint trees. The first is the resource-forest constraint, where we assume that a subset \({\mathtt{R}}\subseteq {\mathcal{V}}\) of the vertices are resource vertices. The constraint specifies that each tree in the forest must contain at least one resource vertex. This is the natural undirected counterpart of the tree constraint [1], which partitions a directed graph into a forest of directed trees where only certain vertices can be tree roots. We describe a hybrid-Consistency algorithm that runs in \({\mathop{\cal O}}(m+n)\) time for the resource forest constraint, a sharp improvement over the \({\mathop{\cal O}}(mn)\) bound that is known for the directed case. The second constraint is proper-forest. In this variant, we do not have the requirement that each tree contains a resource, but the forest must contain only proper trees, i.e., trees that have at least two vertices each. We develop a hybrid-Consistency algorithm for this case whose running time is \({\mathop{\cal O}}(mn)\) in the worst case, and \({\mathop{\cal O}}(m\sqrt{n})\) in many (typical) cases.

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References

  1. Beldiceanu, N., Flener, P., Lorca, X.: The tree Constraint. In: Barták, R., Milano, M. (eds.) CPAIOR 2005. LNCS, vol. 3524, pp. 64–78. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  2. Laurière, J.-L.: A language and a program for stating and solving combinatorial problems. Artificial Intelligence 10, 29–127 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  3. Beldiceanu, N., Contejean, E.: Introducing global constraint in CHIP. Mathl. Comput. Modelling 20(12), 97–123 (1994)

    Article  MATH  Google Scholar 

  4. Sellmann, M.: Cost-based filtering for shortest path constraints. In: Rossi, F. (ed.) CP 2003. LNCS, vol. 2833, pp. 694–708. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  5. Dincbas, M., Van Hentenryck, P., Simonis, H., Aggoun, A., Graf, T., Berthier, F.: The Constraint Logic Programming Language CHIP. In: Int. Conf. on Fifth Generation Computer Systems (FGCS 1988), Tokyo, Japan, pp. 693–702 (1988)

    Google Scholar 

  6. Puget, J.-F.: A C++ Implementation of CLP. In: Second Singapore International Conference on Intelligent Systems (SPICIS), Singapore, November 1994, pp. 256–261 (1994)

    Google Scholar 

  7. Cayley, A.: A theorem on trees. Quart. J. Math. 23, 376–378 (1889)

    MATH  Google Scholar 

  8. Bessière, C., Hebrard, E., Hnich, B., Kızıltan, Z., Walsh, T.: The range and roots Constraints: Specifying Counting and Occurrence Problems. In: IJCAI 2005, pp. 60–65 (2005)

    Google Scholar 

  9. Berge, C.: Graphes, 2nd edn. Dunod, New York (1985) (in French)

    Google Scholar 

  10. Sellmann, M.: Reduction techniques in Constraint Programming and Combinatorial Optimization. PhD thesis, University of Paderborn (2002)

    Google Scholar 

  11. Régin, J.-C.: A filtering algorithm for constraints of difference in CSP. In: AAAI 1994, pp. 362–367 (1994)

    Google Scholar 

  12. Gondran, M., Minoux, M.: Graphes et algorithmes, 2nd edn. Eyrolles, Paris (1985) (in French)

    Google Scholar 

  13. Micali, S., Vazirani, V.V.: An \(\mathcal{O}(\sqrt{|V|} \cdot |{E}|)\) algorithm for finding maximum matching in general graphs. In: FOCS 1980, New York, pp. 17–27. IEEE, Los Alamitos (1980)

    Google Scholar 

  14. Beldiceanu, N., Petit, T., Rochart, G.: Bounds of Graph Characteristics. In: van Beek, P. (ed.) CP 2005. LNCS, vol. 3709, pp. 742–746. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

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Beldiceanu, N., Katriel, I., Lorca, X. (2006). Undirected Forest Constraints. In: Beck, J.C., Smith, B.M. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2006. Lecture Notes in Computer Science, vol 3990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11757375_5

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  • DOI: https://doi.org/10.1007/11757375_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34306-6

  • Online ISBN: 978-3-540-34307-3

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