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Tree-Deletion Pruning in Label-Correcting Algorithms for the Multiobjective Shortest Path Problem

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WALCOM: Algorithms and Computation (WALCOM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10167))

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Abstract

In this paper, we consider algorithms for multi-objective shortest-path (MOSP) optimization in spatial decision making. We re-evaluate the basic strategies for label-correcting algorithms for the MOSP problem, i.e., node and label selection. In contrast to common believe, we show that—when carefully implemented—the node-selection strategy usually beats the label-selection strategy. Moreover, we present a new pruning method which is easy to implement and performs very well on real-world road networks. In this study, we test our hypotheses on artificial MOSP instances from the literature with up to 15 objectives and real-world road networks with up to almost 160,000 nodes. We also evaluate these algorithms on the problem of finding good power grid lines.

F. Bökler—The author has been supported by the Bundesministerium für Wirtschaft und Energie (BMWi) within the research project “Bewertung und Planung von Stromnetzen” (promotional reference 03ET7505) and by DFG GRK 1855 (DOTS).

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Authors and Affiliations

  1. Department of Computer Science, TU Dortmund, Dortmund, Germany

    Fritz Bökler & Petra Mutzel

Authors
  1. Fritz Bökler
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  2. Petra Mutzel
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Correspondence to Fritz Bökler .

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Editors and Affiliations

  1. Universiti Teknologi Brunei, Bandar Seri Begawan, Brunei Darussalam

    Sheung-Hung Poon

  2. Bangladesh University of Engineering and Technology, Dhaka, Bangladesh

    Md. Saidur Rahman

  3. National Taiwan University, Taipei, Taiwan

    Hsu-Chun Yen

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Bökler, F., Mutzel, P. (2017). Tree-Deletion Pruning in Label-Correcting Algorithms for the Multiobjective Shortest Path Problem. In: Poon, SH., Rahman, M., Yen, HC. (eds) WALCOM: Algorithms and Computation. WALCOM 2017. Lecture Notes in Computer Science(), vol 10167. Springer, Cham. https://doi.org/10.1007/978-3-319-53925-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-53925-6_15

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  • Online ISBN: 978-3-319-53925-6

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