Parallelism may reduce the time to find exact solutions for many Operations Research (OR) problems, but parallelising combinatorial search is extremely challenging. YewPar is a new combinatorial search framework designed to allow domain specialists to benefit from parallelism by reusing sophisticated parallel search patterns. This paper shows (1) that it is low effort to encode and parallelise a typical OR problem (Flowshop Scheduling FSP) in YewPar even for scalable clusters; (2) that the YewPar library makes it extremely easy to exploit three alternate FSP parallelisations; (3) that the YewPar FSP implementations are valid, and have sequential performance comparable with a published algorithm; and (4) provides a systematic performance evaluation of the three parallel FSP versions on 10 standard FSP instances with up to 240 workers on a Beowulf cluster.

翻译：平行主义可能会缩短为许多业务研究(OR)问题寻找确切解决方案的时间,但平行的组合搜索却极具挑战性。 YewPar是一个新的组合搜索框架,旨在让域专家通过重复使用复杂的平行搜索模式从平行搜索中受益。 本文显示:(1) 在YewPar对一个典型的OR问题进行编码和平行化的难度很小,即使对于可缩放的集群也是如此;(2) YewPar 图书馆使得利用三种替代的FSP平行化极为容易;(3) YewPar FSP的实施是有效的,其顺序性能与已公布的算法相仿;(4) 系统评估在10个标准FSP案例中的3个平行FSP版本,在Beowulf 集群上有多达240名工人。