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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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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