## 2017 |

Cintrano, Christian; Chicano, Francisco; Alba, Enrique Robust Bi-objective Shortest Path Problem in Real Road Networks Incollection International Conference on Smart Cities, Smart-CT 2017, pp. 128–136, Springer, Cham, 2017, ISBN: 978-3-319-59513-9. Abstract | Links | BibTeX | Tags: Bi-objective shortest path, Multi-objective optimization, Robustness, Traffic road network @incollection{Cintrano2017, title = {Robust Bi-objective Shortest Path Problem in Real Road Networks}, author = {Christian Cintrano and Francisco Chicano and Enrique Alba}, doi = {10.1007/978-3-319-59513-9_13}, isbn = {978-3-319-59513-9}, year = {2017}, date = {2017-06-01}, booktitle = {International Conference on Smart Cities, Smart-CT 2017}, pages = {128--136}, publisher = {Springer, Cham}, edition = {Lecture No}, 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.}, keywords = {Bi-objective shortest path, Multi-objective optimization, Robustness, Traffic road network}, pubstate = {published}, tppubtype = {incollection} } 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. |

## 2017 |

Robust Bi-objective Shortest Path Problem in Real Road Networks Incollection International Conference on Smart Cities, Smart-CT 2017, pp. 128–136, Springer, Cham, 2017, ISBN: 978-3-319-59513-9. |