Optimization of Urban Railway Transit Systems: An Integrated Approach for ‎Simultaneous Enhancement of Energy Efficiency and Travel Time under ‎Uncertainty

Articles in Press

Document Type : Original Article

Authors

1 خیابان مطهری- تقاطع خیابان مفتح- جنب رستوران غنچه- پلاک 220- مرکز علمی و کاربردی حمل و نقل ترافیک تهران-

2 Department of Energy Engineering and Sustainable Resources, College of Interdisciplinary Science and ‎Technology, University of Tehran, Tehran, Iran.‎

10.22059/ses.2026.413703.1235

Abstract

Urban rail systems face the challenge of high energy consumption and the inability of fixed schedules to ‎adapt to real-time demand changes (especially under variable weather conditions). This study presents an ‎integrated framework comprising a demand prediction model and a multi-objective optimization engine to ‎develop energy-efficient operational strategies. The demand model, based on Random Forest regression, ‎generates realistic scenarios by combining temporal patterns, meteorological data, and real passenger ‎statistics. The optimization engine, based on the Differential Evolution algorithm, adjusts train schedules and ‎speed profiles to reduce energy consumption and maintain service quality (headway evenness). Implementing ‎this framework on a day with severe weather conditions showed that daily energy consumption was reduced ‎by 11.46%, and CO2emissions decreased by 13.45 tons. Simultaneously, the average passenger travel time ‎decreased by 12.51%, overcoming the trade-off between energy efficiency and service speed. Sensitivity ‎analysis revealed that time (hour) and snowfall have the greatest impact on passenger load. This scenario-‎based approach simultaneously improves environmental performance and service quality.‎

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Journal of sustainable Energy Systems

Articles in Press, Accepted Manuscript
Available Online from 29 May 2026

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