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Solving the sequential ordering problem using branch and bound

机译:使用分支定界法解决顺序排序问题

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The Sequential Ordering Problem (SOP) is an NP-hard problem with a wide range of applications in the domains of scheduling, logistics and compilers. The development of powerful computers and effective algorithmic techniques has made it possible to devise exact algorithms that can solve larger instances of this problem. In this paper, we present an enhanced exact algorithm for this problem using a branch-and-bound (B&B) approach. The proposed algorithm is based on a new lower-bound technique and a local-search domination technique. The new lower-bound technique uses the dynamic Hungarian algorithm to solve a Minimum-Cost Perfect Matching relaxation of the SOP. The local search domination technique prunes the sub-tree below the current node in the B&B tree if a better partial solution is found. The performance of the proposed algorithm is evaluated experimentally using three different benchmark suites: TSPLIB, SOPLIB and COMPILERS. The results of the experimental evaluation show that the proposed algorithm finds exact solutions considerably faster than previously proposed algorithms. The proposed approach significantly reduces the optimality gap to 0.217, 0.122, and 0.004 for the three respective benchmark sets, and closes five instances that were previously open.
机译:顺序排序问题(SOP)是NP难题,在调度,物流和编译器领域具有广泛的应用。强大的计算机和有效的算法技术的发展使人们有可能设计出可以解决该问题的更多实例的精确算法。在本文中,我们使用分支定界(B&B)方法针对此问题提出了一种增强的精确算法。所提出的算法基于一种新的下界技术和局部搜索支配技术。新的下限技术使用动态匈牙利算法来解决SOP的最小成本完美匹配松弛问题。如果找到更好的局部解决方案,则本地搜索控制技术会修剪B&B树中当前节点下方的子树。使用三种不同的基准套件(TSPLIB,SOPLIB和COMPILERS)对所提出算法的性能进行了实验评估。实验评估的结果表明,与先前提出的算法相比,所提出的算法找到精确解的速度要快得多。对于三个各自的基准集,所提出的方法将最佳差距显着减小到0.217、0.122和0.004,并关闭了先前打开的五个实例。

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