2026-04-14T02:52:24Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/3846472026-01-21T09:58:21Zcom_2072_1033col_2072_452950

Combining survival analysis and simheuristics to predict the risk of delays in urban ridesharing operations with random travel times Herrera Machado, Erika Magdalena Panadero Martínez, Javier Carracedo Garnateo, Patricia Juan, Angel A. Torre Martínez, María del Rocío de la Perez Bernabeu, Elena Universitat Politècnica de Catalunya. Departament d'Organització d'Empreses Àrees temàtiques de la UPC::Economia i organització d'empreses Transportation -- Environmental aspects Mobilitat sostenible © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works More sustainable transportation and mobility concepts, such as ridesharing, are gaining momentum in modern smart cities. In many real-life scenarios, travel times among potential customers' locations should be modeled as random variables. This uncertainty makes it difficult to design efficient ridesharing schedules and routing plans, since the risk of possible delays has to be considered as well. In this paper, we model ridesharing as a stochastic team orienteering problem in which the trade-off between maximizing the expected reward and the risk of incurring time delays is analyzed. In order to do so, we propose a simulation-optimization approach that combines a simheuristic algorithm with survival analysis techniques. The aforementioned methodology allows us to generate not only the probability that a given routing plan will suffer a delay, but also gives us the probability that the routing plan experiences delays of different sizes. Peer Reviewed Postprint (author's final draft) 2023 Conference report Herrera, E. [et al.]. Combining survival analysis and simheuristics to predict the risk of delays in urban ridesharing operations with random travel times. A: Winter Simulation Conference. "Proceedings of the 2022 Winter Simulation Conference". p. 1660-1671. DOI 10.1109/WSC57314.2022.10015474. https://hdl.handle.net/2117/384647 10.1109/WSC57314.2022.10015474 eng https://ieeexplore.ieee.org/document/10015474 http://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access Attribution-NonCommercial-NoDerivatives 4.0 International 12 p. application/pdf application/pdf