Abstract
ABSTRACT Proactive demand management methods can achieve a trade-off between supply and demand for high-speed railways. Focusing on multi-type demand configurations, four active demand management methods were designed, two single-scenario and two multi-scenario methods. An optimization model of stop planning and seat allocation was constructed to minimize the difference between demand and supply, number of trains, and train-stop costs. The number of train stops, transport capacity, and train occupancy rates were considered. Particle swarm optimization and CPLEX were combined to handle this significant linear programming problem. A real case study of different demand scenarios based on the Hohhot-Beijing high-speed railway in China verified the feasibility of active demand management methods. The results indicate that integrated optimization can be justified with mixed load patterns. Compared with the original scheme, the optimized scheme reduced the number of trains by 23.4% and increased train occupancy rate by more than 36.7%.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
