Robust Bi-objective shortest path problem in real road networks

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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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Cintrano, C., Chicano, F., & Alba, E. (2017). Robust Bi-objective shortest path problem in real road networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10268 LNCS, pp. 128–136). Springer Verlag. https://doi.org/10.1007/978-3-319-59513-9_13

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