利用Bobpp框架解决方案部分控制问题的确定性划分
Partitionnement Déterministe pour Résoudre les Problèmes de Programmation Par Contraintes en utilisant le Framework Parallèle Bobpp
摘要：
本文提出了一种确定性并行化探索约束规划搜索空间。这项工作是一个名为PAJERO的工业项目，这是在需要一个并行约束求解器，总是响应相同的解决方案，无论是使用顺序或并行机的答案。众所周知，并行树搜索改变了对解空间进行探索的顺序。在返回找到的第一个解决方案的上下文中，使用不同数量的核可能会改变返回的解决方案。在文献中，已经提出了几种非确定性策略来并行化约束编程搜索空间的探索。它们中的大多数都是基于工作窃取技术，该技术用于根据需求和在搜索算法执行期间划分约束编程搜索空间。我们的研究集中在并行搜索与顺序搜索的决定论。我们认为，顺序搜索算法是确定性的，然后提出一个优雅的解决方案，引入一个总顺序的节点，其中的并行算法总是给出相同的解决方案，顺序的，无论使用的核心数量。为了评估这种确定性策略，我们在并行Bobpp框架上使用Google OR-Tools约束编程求解器进行了测试。通过求解FlatZinc格式建模的约束编程问题来说明性能。
英文摘要：
This paper presents a deterministic parallelization to explore a Constraint Programming search space. This work is an answer to an industrial project named PAJERO, which is in need of a parallel constraint solver which always responds with the same solution whether using sequential or parallel machines. It is well known that parallel tree search changes the order in which the exploration of solution space is done. In the context where the first solution found is returned, using a different number of cores may change the returned solution. In the literature, several non deterministic strategies have been proposed to parallelize the exploration of Constraint Programming search space. Most of them are based on the Work Stealing technique used to partition the Constraint Programming search space on demand and during the execution of the search algorithm. Our study focuses on the determinism of the parallel search versus the sequential one. We consider that the sequential search algorithm is deterministic, then propose an elegant solution introducing a total order on the nodes in which the parallel algorithm always gives the same solution as the sequential one regardless of the number of cores used. To evaluate this deterministic strategy, we ran tests using the Google OR-Tools Constraint Programming solver on top of our parallel Bobpp framework. The performances are illustrated by solving Constraint Programming problems modeled in FlatZinc format.
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