A Multi-Objective Train Operational Plan Optimization Approach for Adding Additional Trains on a High-Speed Railway Corridor in Peak Periods

Passenger demand for railway transportation rapidly increases in peak periods, and the transport capacity for existing trains is not sufficient. Railway companies usually adopt the strategy of adding additional trains in peak periods to meet the higher passenger demand. Designing a good operational...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Applied sciences Ročník 10; číslo 16; s. 5554
Hlavní autori: Liu, Yutong, Cao, Chengxuan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.08.2020
Predmet:
ISSN:2076-3417, 2076-3417
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Passenger demand for railway transportation rapidly increases in peak periods, and the transport capacity for existing trains is not sufficient. Railway companies usually adopt the strategy of adding additional trains in peak periods to meet the higher passenger demand. Designing a good operational plan for additional trains becomes a challenge for operators, though. A new optimization approach for designing an operational plan for additional trains is proposed in this paper. The number of trains, the operational plan, the stop plan, and the timetable for each train can be considered simultaneously in the new optimization approach, which will make it easier to design an operational plan for additional trains. A multi-objective nonlinear model with three objectives of minimizing total running distance, dwelling time, and unsatisfied passengers is proposed. Big-M is introduced to transform the nonlinear model into a linear model. The solver CPLEX is used to solve the transformed linear model and obtain the optimal operational plan. Small-scale numerical experiments are implemented to show the effectiveness of the optimization approach. The large-scale case of the Beijing‒Shanghai railway corridor is studied to demonstrate that the optimization approach can be applied to real-word and large-scale situations.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app10165554