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Title: A bi-objective reliable path-finding algorithm for battery electric vehicle routing
Authors: Chen, XW 
Chen, BY 
Lam, WHK 
Tam, ML 
Ma, W 
Issue Date: 11-Nov-2021
Source: Expert systems with applications, 11 Nov. 2021, v. 182, 115228
Abstract: This paper proposes a bi-objective reliable path-finding algorithm for routing battery electric vehicles on a road network, with vehicles’ energy consumption uncertainty and travel time uncertainty. A bi-objective stochastic optimization problem is proposed and formulated to simultaneously maximize energy consumption reliability (ECR) and travel time reliability (TTR). ECR is defined as the probability of finishing a trip without exhausting a given battery energy budget, while TTR is the on-time arrival probability with the travel time budget. In this study, the proposed optimization problem is decomposed into two sub-problems: (1) finding K most reliable paths for maximizing the TTR objective and (2) finding the most reliable path for optimizing the ECR objective. Then, a novel ranking algorithm is proposed to exactly solve the formulated optimization problem. A case study is carried out on Hong Kong's road network to demonstrate the efficacy and efficiency of the proposed algorithm for real-world applications.
Keywords: Bi-objective path finding
Energy consumption reliability
Network uncertainties
Travel time reliability
Publisher: Pergamon Press
Journal: Expert systems with applications 
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2021.115228
Rights: © 2021 Elsevier Ltd. All rights reserved.
© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.
The following publication Chen, X.-W., et al. (2021). "A bi-objective reliable path-finding algorithm for battery electric vehicle routing." Expert Systems with Applications 182: 115228 is available at https://dx.doi.org/10.1016/j.eswa.2021.115228.
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