Reconfiguring Shortest Paths in Graphs

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Algorithmica Pub Date : 2024-08-27 DOI:10.1007/s00453-024-01263-y
Kshitij Gajjar, Agastya Vibhuti Jha, Manish Kumar, Abhiruk Lahiri
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Abstract

Reconfiguring two shortest paths in a graph means modifying one shortest path to the other by changing one vertex at a time so that all the intermediate paths are also shortest paths. This problem has several natural applications, namely: (a) repaving road networks, (b) rerouting data packets in a synchronous multiprocessing setting, (c) the shipping container stowage problem, and (d) the train marshalling problem. When modelled as graph problems, (a) is the most general case while (b), (c), (d) are restrictions to different graph classes. We show that (a) does not admit polynomial-time algorithms (assuming \({{\,\mathrm{\texttt {P}}\,}}\ne {{\,\mathrm{\texttt {NP}}\,}}\)), even for relaxed variants of the problem (assuming \({{\,\mathrm{\texttt {P}}\,}}\ne {{\,\mathrm{\texttt {PSPACE}}\,}}\)). For (b), (c), (d), we present polynomial-time algorithms to solve the respective problems. We also generalize the problem to when at most k (for a fixed integer \(k\ge 2\)) contiguous vertices on a shortest path can be changed at a time.

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重新配置图中的最短路径
重新配置图中的两条最短路径是指通过每次改变一个顶点,将一条最短路径修改为另一条最短路径,从而使所有中间路径也成为最短路径。这个问题有几种自然应用,即:(a) 重铺道路网络,(b) 同步多处理设置中的数据包重新路由,(c) 船运集装箱堆放问题,以及 (d) 火车调度问题。以图问题建模时,(a) 是最一般的情况,而(b)、(c)、(d) 则是对不同图类的限制。我们证明(a)不允许多项式时间算法(假设({{,\mathrm{texttt {P}}\,}}ne {{,\mathrm{texttt {NP}}\、),甚至对于问题的宽松变体(假定 ({{\,\mathrm{texttt {P}}\,}}ne {{\,\mathrm{texttt {PSPACE}}\,}}\)).对于 (b)、(c)、(d),我们提出了解决相应问题的多项式时间算法。我们还将问题推广到最短路径上最多有 k 个(对于固定整数 \(k\ge2\))连续顶点可以同时改变。
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来源期刊
Algorithmica
Algorithmica 工程技术-计算机:软件工程
CiteScore
2.80
自引率
9.10%
发文量
158
审稿时长
12 months
期刊介绍: Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential. Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming. In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.
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