Reconfiguring Shortest Paths in Graphs
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Published:2024-08-27
Issue:
Volume:
Page:
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ISSN:0178-4617
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Container-title:Algorithmica
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language:en
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Short-container-title:Algorithmica
Author:
Gajjar Kshitij,Jha Agastya Vibhuti,Kumar Manish,Lahiri Abhiruk
Abstract
AbstractReconfiguring 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 $${{\,\mathrm{\texttt {P}}\,}}\ne {{\,\mathrm{\texttt {NP}}\,}}$$
P
≠
NP
), even for relaxed variants of the problem (assuming $${{\,\mathrm{\texttt {P}}\,}}\ne {{\,\mathrm{\texttt {PSPACE}}\,}}$$
P
≠
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 $$k\ge 2$$
k
≥
2
) contiguous vertices on a shortest path can be changed at a time.
Funder
H2020 European Research Council Faculty of Science, National University of Singapore Rita Altura Trust Chair Lynne and William Frankel Center for Computer Science Israel Science Foundation Ministerstvo Školství, Mládeže a Tělovýchovy Charles University
Publisher
Springer Science and Business Media LLC
Reference64 articles.
1. Gajjar, K., Jha, A.V., Kumar, M., Lahiri, A.: Reconfiguring shortest paths in graphs. In: Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, Virtual Event, February 22–March 1, 2022, pp. 9758–9766. AAAI Press, USA. https://ojs.aaai.org/index.php/AAAI/article/view/21211 (2022) 2. Ratner, D., Warmuth, M.K.: Finding a shortest solution for the N $${\times }$$ N extension of the 15-puzzle is intractable. In: Proceedings of the 5th National Conference on Artificial Intelligence. Philadelphia, PA, USA, August 11-15, 1986. Volume 1: Science, USA, pp. 168–172. http://www.aaai.org/Library/AAAI/1986/aaai86-027.php (1986) 3. Goldreich, O.: Finding the shortest move-sequence in the graph-generalized 15-puzzle is np-hard. In: Studies in Complexity and Cryptography. Miscellanea on the Interplay Between Randomness and Computation - In Collaboration with Lidor Avigad, Mihir Bellare, Zvika Brakerski, Shafi Goldwasser, Shai Halevi, Tali Kaufman, Leonid Levin, Noam Nisan, Dana Ron, Madhu Sudan, Luca Trevisan, Salil Vadhan, Avi Wigderson, David Zuckerman. Lecture Notes in Computer Science, vol. 6650, pp. 1–5. Springer, USA. https://doi.org/10.1007/978-3-642-22670-0_1 (2011) 4. Demaine, E.D., Demaine, M.L., Eisenstat, S., Lubiw, A., Winslow, A.: Algorithms for solving rubik’s cubes. In: Algorithms–ESA 2011–19th Annual European Symposium, Saarbrücken, Germany, September 5-9, 2011. Proceedings. Lecture Notes in Computer Science, vol. 6942, pp. 689–700. https://doi.org/10.1007/978-3-642-23719-5_58 (2011) 5. Demaine, E.D., Eisenstat, S., Rudoy, M.: Solving the rubik’s cube optimally is np-complete. In: 35th Symposium on Theoretical Aspects of Computer Science, STACS 2018, February 28 to March 3, 2018, Caen, France. LIPIcs, vol. 96, pp. 24–12413. Dagstuhl, Germany. https://doi.org/10.4230/LIPIcs.STACS.2018.24 (2018)
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