Skip to main content

Partitioning Methods to Parallelize Constraint Programming Solver Using the Parallel Framework Bobpp

  • Conference paper

Part of the book series: Studies in Computational Intelligence ((SCI,volume 479))

Abstract

This paper presents a parallelization of a Constraint Programming solver, OR-Tools, using the parallel framework Bobpp [2].

An argument in support of this approach is that the parallelization of algorithms searching for solutions in the research area is extensively studied over the world.

The novelty presented here is the study of a parallelization for which the control of the OR-Tools sequential search is limited. Using OR-Tools, it is possible to record the path from the tree’s root to a node so as to stop the search at a precise node. However, to start the search on a subtree, the entire path from the root of the main tree to the root of the sub-tree has to be replayed. This suggests that this leads to additional costs during the search.

To thwart this problem, different strategies of load balancing are tried to reduce the extra costs due to the redundant branches.

This work is funded by ”PAJERO” OSEO-ISI project.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anstreicher, K., Brixius, N., Goux, J.-P., Linderoth, J.: Solving large quadratic assignment problems on computational grids (2000)

    Google Scholar 

  2. Bertrand Le Cun, P.V.-S., Menouer, T.: Bobpp, http://forge.prism.uvsq.fr/projects/bobpp

  3. Gendron, B., Crainic, T.G.: Parallel branch-and-bound algorithms: Survey and synthesis. Operational Research 42(06), 1042–1066 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  4. Cung, V.-D., Dowaji, S., Le, C.B., Mautor, T., Roucairol, C.: Concurrent data structures and load balancing strategies for parallel branch-and-bound / a* algorithms. In: III Annual Implementation Challenge Workshop, DIMACS, New Brunswick, USA (October 1994)

    Google Scholar 

  5. Miller, D.L., Pekny, J.F.: Results from a parallel branch and bound algorithm for the asymmetric traveling salesman problem. Technical report, Carnegie Mellon University, PITTSBURGH, PA 15212 (1989)

    Google Scholar 

  6. Eckstein, J., Phillips, C.A., Hart, W.E.: PEBBL 1.0 User Guide. RRR 19-2006, RUTCOR (August 2006)

    Google Scholar 

  7. Feldmann, R.: Game Tree Search on Massively Parallel Systems. PhD thesis, Department of mathematics and computer science, University of Paderborn, Germany (August 1993)

    Google Scholar 

  8. Finkel, R., Manber, U.: Dib- a distributed implementation of backtracking. ACM, Transaction on Programming Languages and Systems 9(02), 235–256 (1987)

    Article  Google Scholar 

  9. Galea, F., Le Cun, B.: Bob++: a framework for exact combinatorial optimization methods on parallel machines. In: International Conference High Performance Computing & Simulation 2007 (HPCS 2007) and in conjunction with The 21st European Conference on Modeling and Simulation (ECMS 2007), pp. 779–785 (June 2007)

    Google Scholar 

  10. Eckstein, J., Phillips, C.A., Hart, W.E.: PICO: An object-oriented framework for parallel branch and bound. In: Scientific, E. (ed.) Proceedings of the Workshop on Inherently Parallel Algorithms in Optimization and Feasibility and their Applications. Studies in Computational Mathematics, pp. 219–265 (2001)

    Google Scholar 

  11. Kumar, V., Ramesh, K., Rao, V.N.: Parallel best-first search of state-space graphs : A summary of results. In: The AAAI Conference, pp. 122–127 (1987)

    Google Scholar 

  12. Lai, T., Sprague, A.: Performance of parallel branch-and-bound algorithms. IEEE Transactions On Computers C-34(10), 962–964 (1985)

    Article  Google Scholar 

  13. Le Cun, B., Roucairol, C.: Concurrent data structures for tree search algorithms. In: Ferreira, K.A.A., Rolim, J. (eds.) IFIP WG 10.3, IRREGULAR 1994: Parallel Algorithms for Irregular Structured Problems, pp. 135–155 (September 1994)

    Google Scholar 

  14. Le Cun, B., Roucairol, C., the PNN team. Bob: a unified platform for implementing branch-and-bound like algorithms. RR 95/16, Laboratoire PRiSM, Université de Versailles - Saint Quentin en Yvelines (September 1995)

    Google Scholar 

  15. Michel, L., See, A., Van Hentenryck, P.: Transparent parallelization of constraint programming. Informs Journal on Computing 21(3), 363–382 (2009)

    Article  MATH  Google Scholar 

  16. van Omme, V.F.N., Perron, L.: Or-tools. Technical report, Google (2012)

    Google Scholar 

  17. Gent, I.P., Jefferson, C., Miguel, I., Moore, N.C., Nightingale, P., Prosser, P., Unsworth, C.: A preliminary review of literature on parallel constraint solving. In: Proceedings PMCS 2011 Workshop on Parallel Methods for Constraint Solving (2011)

    Google Scholar 

  18. Ralphs, T., Ladányi, L., Saltzman, M.: A Library Hierarchy for Implementing Scalable Parallel Search algorithms. The Journal of Supercomputing 28(2), 215–234 (2004)

    Article  MATH  Google Scholar 

  19. Ladányi, L., Ralphs, T.K., Trotter Jr., L.E.: Branch, cut, and price: Sequential and parallel. In: Jünger, M., Naddef, D. (eds.) Computat. Comb. Optimization. LNCS, vol. 2241, pp. 223–260. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  20. Rolf, C.C.: Parallelism in Constraint Programming. PhD thesis, Department of Computer Science, Lund University (October 2011)

    Google Scholar 

  21. Saltzman, M.J.: COIN-OR: An Open Source Library for optimization. In: Advances in Computational Economics. Kluwer, Boston (2002)

    Google Scholar 

  22. Shinano, Y., Higaki, M., Hirabayashi, R.: An Interface Design for General Parallel Branch-and-Bound Algorithms. In: Workshop on Parallel Algorithms for Irregularly Structured Problems, pp. 277–284 (1996)

    Google Scholar 

  23. Shinano, Y., Higari, M., Hirabayashi, R.: Generalized utility for parallel branch-and-bound algorithms. In: Proceedings of the 1995 Seventh Symposium on Parallel and Distributed Processing, pp. 392–401. IEEE Computer Society Press, Los Alamitos (1995)

    Chapter  Google Scholar 

  24. Ralphs, T.K., Ladányi, L., Saltzman, M.: Parallel Branch, Cut, and Price for Large-scale Discrete Optimization. Mathematical Programming 98(253) (2003)

    Google Scholar 

  25. Tschoke, S., Polzer, T.: Portable parallel branch-and-bound library user manual, library version 2.0. Technical report, Department of Computer Sciences, University of Paderborn (1996)

    Google Scholar 

  26. Vander-Swalmen, P., Dequen, G., Krajecki, M.: Designing a parallel collaborative sat solver. In: 17th International Conference on Parallel and Distributed Processing Techniques and Applications, USA, CSREA Press (2011)

    Google Scholar 

  27. Wetzel, G., Zabatta, F.: A constraint programming approach to portfolio selection. In: Proceeding of the 13th Biennial European Conference on Artificial Intelligence, pp. 263–264 (1998)

    Google Scholar 

  28. Xu, Y., Ralphs, T., Ladányi, L., Saltzman, M.: ALPS: A Framework for Implementing Parallel Search Algorithms. In: Proceedings of the Ninth INFORMS Computing Society Conference (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tarek Menouer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Menouer, T., Le Cun, B., Vander-Swalmen, P. (2013). Partitioning Methods to Parallelize Constraint Programming Solver Using the Parallel Framework Bobpp. In: Nguyen, N., van Do, T., le Thi, H. (eds) Advanced Computational Methods for Knowledge Engineering. Studies in Computational Intelligence, vol 479. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00293-4_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00293-4_10

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00292-7

  • Online ISBN: 978-3-319-00293-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics