Abstract
The present study focuses on the development of a multi-objective optimization scheme to improve the efficiency of railway systems. This is achieved through the identification of the optimal train speed profiles employing a novel modeling framework based on Data Envelopment Analysis (DEA). Train speed profiles are selected with the objective to transfer more passengers in less time and with less energy under scheduling constraints. Given that DEA is a data oriented, non-parametric method, a large-scale experimental camping has been carried out over an operational tramway system to collect the required inputs/outputs. Numerical results show that when the proposed approach energy consumption can be reduced by 10%.
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Acknowledgement
The present study has received funding from the European Union’s Horizon 2020 research and innovation programme IN2DREAMS under grant agreement No: 777596 and IN2STEMPO under grant 777515.
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Achilleos, A. et al. (2021). Multi-objective Optimization of Train Speed Profiles Using History Measurements. In: Helfert, M., Klein, C., Donnellan, B., Gusikhin, O. (eds) Smart Cities, Green Technologies and Intelligent Transport Systems. SMARTGREENS VEHITS 2019 2019. Communications in Computer and Information Science, vol 1217. Springer, Cham. https://doi.org/10.1007/978-3-030-68028-2_17
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DOI: https://doi.org/10.1007/978-3-030-68028-2_17
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