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A Distributed Heuristic Algorithm for the Rectilinear Steiner Minimal Tree Problem

机译:线性Steiner最小树问题的分布式启发式算法。

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Rectilinear Steiner minimal tree (RSMT) problem finds a minimum length tree that interconnects a given set of points by only horizontal and vertical line segments and by using extra points if necessary. In this paper, to speedup the RSMT construction, two recently developed successful heuristic algorithms, namely rectilinear steiner tree (RST) by Zhou and batched greedy algorithm (BGA) by Kahng , have been used as the basis. Following a slight modification on RST, which led to a nonrecursive and a considerably faster version, a partially parallelized and distributed form of this modified algorithm is proposed. Computational tests using large random data sets have shown the advantage of the modification on RST, and tests conducted on a cluster of workstations have proven the proposed distributed approach to be very promising particularly for large problem instances.
机译:直线斯坦纳最小树(RSMT)问题找到了最小长度树,该树仅通过水平和垂直线段以及必要时使用额外的点来互连给定点集。在本文中,为了加快RSMT的构建,已经使用了两个最近成功开发的启发式算法,分别是Zhou的直线斯坦纳树(RST)和Kahng的批量贪婪算法(BGA)作为基础。在对RST进行细微修改之后,导致了非递归和相当快的版本,提出了此修改算法的部分并行化和分布式形式。使用大型随机数据集的计算测试显示了对RST进行修改的优势,并且在一组工作站上进行的测试证明了所提出的分布式方法非常有希望,特别是对于大型问题实例。

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