Abstract
Road journeys are one of our most frequent daily tasks. Despite we need them, these trips have some associated costs: time, money, pollution, etc. One of the usual ways of modeling the road network is as a graph. The shortest path problem consists in finding the path in a graph that minimizes a certain cost function. However, in real world applications, more than one objective must be optimized simultaneously (e.g. time and pollution) and the data used in the optimization is not precise: it contains errors. In this paper we propose a new mathematical model for the robust bi-objective shortest path problem. In addition, some empirical studies are included to illustrate the utility of our formulation.
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Notes
- 1.
Official web site: https://www.openstreetmap.org.
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Acknowledgements
This research was partially funded by the University of Málaga, Andalucía Tech, and the Spanish Ministry of Economy and Competitiveness and FEDER (grant TIN2014-57341-R).
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Cintrano, C., Chicano, F., Alba, E. (2017). Robust Bi-objective Shortest Path Problem in Real Road Networks. In: Alba, E., Chicano, F., Luque, G. (eds) Smart Cities. Smart-CT 2017. Lecture Notes in Computer Science(), vol 10268. Springer, Cham. https://doi.org/10.1007/978-3-319-59513-9_13
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DOI: https://doi.org/10.1007/978-3-319-59513-9_13
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