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