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一种用于带容量限制的斯坦纳树问题的构造启发式算法。

A construction heuristic for the capacitated Steiner tree problem.

机构信息

IDLab, Ghent University - imec, Ghent, Belgium.

出版信息

PLoS One. 2022 Jun 16;17(6):e0270147. doi: 10.1371/journal.pone.0270147. eCollection 2022.

Abstract

Many real-life problems boil down to a variant of the Minimum Steiner Tree Problem (STP). In telecommunications, Fiber-To-The-Home (FTTH) houses are clustered so they can be connected with fiber as cost-efficiently as possible. The cost calculation of a fiber installment can be formulated as a capacitated STP. Often, STP variants are solved with integer linear programs, which provide excellent solutions, though the running time costs increase quickly with graph size. Some geographical areas require graphs of over 20000 nodes-typically unattainable for integer linear programs. This paper presents an alternative approach. It extends the shortest path heuristic for the STP to a new heuristic that can construct solutions for the capacitated STP: the Capacitated Shortest Path Heuristic (CSPH). It is straightforward to implement, allowing many extensions. In experiments on realistic telecommunications datasets, CSPH finds solutions on average in time O(|V|2), quadratic in the number of nodes, making it possible to solve 50000 node graphs in under a minute.

摘要

许多现实生活中的问题可以归结为最小斯坦纳树问题 (STP) 的变体。在电信中,光纤到户 (FTTH) 房屋被聚类,以便可以尽可能高效地用光纤连接。光纤安装的成本计算可以被公式化为有容量限制的 STP。通常,STP 的变体可以用整数线性规划来解决,这提供了极好的解决方案,尽管随着图规模的增加,运行时间成本会迅速增加。一些地理区域需要超过 20000 个节点的图 - 通常对于整数线性规划来说是无法实现的。本文提出了一种替代方法。它将 STP 的最短路径启发式扩展到一种新的启发式方法,该方法可以为有容量限制的 STP 构建解决方案:有容量限制的最短路径启发式 (CSPH)。它易于实现,允许许多扩展。在对现实电信数据集的实验中,CSPH 平均在 O(|V|2)的时间内找到解决方案,这是节点数量的二次方,使得在不到一分钟的时间内就可以解决 50000 个节点的图。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e97d/9202893/2226fb7d3320/pone.0270147.g001.jpg

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