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Published in:

2018 | OriginalPaper | Chapter

Solving the Time-Dependent Shortest Path Problem Using Super-Optimal Wind

Author : Adam Schienle

Published in: Operations Research Proceedings 2017

Publisher: Springer International Publishing

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Abstract

Planning efficient routes fast becomes ever more important, especially in the context of aircraft trajectories. As time-dependent wind conditions factor into the shortest path query, we use an artificial wind vector called Super-Optimal Wind as a means of creating a suitable potential function for the A* algorithm, thus speeding up the query. We assess the quality of Super-Optimal Wind both theoretically and computationally, and use Super-Optimal Wind in a real-world instance.

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next chapter Anticipation in Dynamic Vehicle Routing
Footnotes
1
Speed relative to the surrounding air mass.
 
Literature
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Bast, H., Delling, D., Goldberg, A., Müller-Hannemann, M., Pajor, T., Sanders, P., Wagner, D., & Werneck, R. F. (2015). Route planning in transportation networks. Technical report, Microsoft Research. Updated version of the technical report MSR-TR-2014-4.
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Blanco, M., Borndörfer, R., Hoang, N. D., Kaier, A., Schienle, A., Schlechte, T., & Sclobach, S. (2016). Solving time dependent shortest path problems on airway networks using super-optimal wind. 16th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2016), 54. (epub ahead of print).
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Goldberg, A. V., & Harrelson, C. (2004). Computing the shortest path: A* search meets graph theory. Technical Report MSR-TR-2004-24, Microsoft Research, Vancouver, Canada, July 2004.
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Hart, P. E., Nilsson, N. J., & Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 4, 100–107.CrossRef
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Schienle, A. (2016). Shortest paths on airway networks. Master’s thesis, Freie Universitt Berlin.
Metadata
Title
Solving the Time-Dependent Shortest Path Problem Using Super-Optimal Wind
Author
Adam Schienle
Copyright Year
2018
Book
Operations Research Proceedings 2017

Print ISBN: 978-3-319-89919-0

Electronic ISBN: 978-3-319-89920-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-89920-6_1

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