Xing, C, Li, K orcid.org/0000-0001-6657-0522, Zhang, L et al. (1 more author) (2023) Robust Optimization of Energy-Saving Train Trajectories under Passenger Load Uncertainty Based on p-NSGA-II. IEEE Transactions on Transportation Electrification, 9 (1). 1826 -1844. ISSN 2332-7782
Abstract
Railway electrification has attracted substantial interests in recent years as a key part of the global effort to achieve transport decarbonisation. To improve the energy efficiency of train operations, of particular interest is the optimization of train speed trajectories. However, most studies formulate the problem as a single-objective optimization model and do not take into account train mass uncertainty associated with the passenger load variations. This paper formulates a bi-objective robust optimization model to minimize both the energy consumption and journey time, in which the robustness against the uncertain train mass is considered and viewed as a decision-maker preference. A novel multi-objective optimization algorithm namely p-NSGA-II is proposed, incorporating the original NSGA-II and a proposed preference dominance criterion to handle the DM preference. With the proposed p-NSGA-II, not only all solutions will converge to the optimal Pareto front but also solutions with better robustness in the Pareto front will be automatically selected and retained, meanwhile the spread of the selected solutions is maintained. The effectiveness of the p-NSGA-II to generate a set of performance-robust driving schemes is verified by numerical case studies. The results show that the p-NSGA-II can achieve up to 40.59% robustness improvement compared to the original NSGA-II.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 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. |
Keywords: | Train energy-saving speed trajectories , robust multi-objective optimization , train load uncertainty , p-NSGA-II |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Aug 2022 11:13 |
Last Modified: | 22 Aug 2024 13:38 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/tte.2022.3194698 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:189547 |