Robust Optimization Method for Mountain Railway Alignments Considering Preference Uncertainty for Costs and Seismic Risks
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 1
Abstract
Railways are vital infrastructures whose design is complex and time-consuming. In addition to multiple conflicting objectives and highly-constrained search spaces, their design also faces great uncertainties. The aim of this study is to optimize railway alignments considering decision-makers’ preference uncertainty for multiple objectives, which can influence the alignment determination macroscopically and fundamentally. First, a multiobjective model is built by integrating costs (including construction and operation costs) and seismic risks (including direct and indirect losses) for mountain railway optimization. To solve this model, a particle swarm algorithm is improved by incorporating a multicriteria tournament decision (MTD). Then, a robust optimization MTD (RO-MTD) method is developed to find cost-risk tradeoffs by addressing the uncertainty of decision-makers’ preferences. The major steps of the RO-MTD include (1) treating uncertain preferences as variables, (2) sampling the uncertain space of preferences, (3) analyzing all possible preference scenarios, and (4) integrating those analyses to achieve a robust evaluation. Finally, the preceding approaches are applied to a complicated real-world case. By comparing the RO-MTD and MTD as well as the computer-generated alignment and the best manually-designed one, the effectiveness of the proposed method is confirmed.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions. All design data for the case study presented here, such as the railway location, manually-design solution, and topographic and seismic information of the study area, are provided by the China Railway Eryuan Engineering Group. These data were provided to support this research but detailed information cannot be presented in this paper because the proprietary rights belong to that company.
However, some alternative topography data can be downloaded from the Geospatial Data Cloud website (http://www.gscloud.cn) and the PGA data can be referred to the Seismic Ground Motion Parameter Zonation Map of China (China Earthquake Administration 2016). These data are available from the corresponding author upon reasonable request.
Acknowledgments
This work is partially funded by the National Science Foundation of China (NSFC) with Award Nos. 51778640 and 52078497, the Project of Science and Technology Research and Development Plan of China National Railway Group with Award No. P2019G003, and the Central South University Special Scholarship for Study Abroad. The authors are grateful to the China Railway Eryuan Engineering Group for supporting them with many real cases.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8 • Issue 1 • March 2022
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© 2021 American Society of Civil Engineers.
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Received: Jun 10, 2021
Accepted: Oct 6, 2021
Published online: Nov 25, 2021
Published in print: Mar 1, 2022
Discussion open until: Apr 25, 2022
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