Abstract
We study the problem of finding multimodal journeys in transportation networks, including unrestricted walking, driving, cycling, and schedule-based public transportation. A natural solution to this problem is to use multicriteria search, but it tends to be slow and to produce too many journeys, several of which are of little value. We propose algorithms to compute a full Pareto set and then score the solutions in a postprocessing step using techniques from fuzzy logic, quickly identifying the most significant journeys. We also propose several (still multicriteria) heuristics to find similar journeys much faster, making the approach practical even for large metropolitan areas.
Partial support by DFG grant WA654/16-1 and EU grant 288094 (eCOMPASS).
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Delling, D., Dibbelt, J., Pajor, T., Wagner, D., Werneck, R.F. (2013). Computing Multimodal Journeys in Practice. In: Bonifaci, V., Demetrescu, C., Marchetti-Spaccamela, A. (eds) Experimental Algorithms. SEA 2013. Lecture Notes in Computer Science, vol 7933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38527-8_24
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DOI: https://doi.org/10.1007/978-3-642-38527-8_24
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