Operation optimizing for minimizing passenger travel time cost and operating cost with time-dependent demand and skip-stop patterns: Nonlinear integer programming model with linear constraints

•Focus on minimizing the total travel time cost by adjusting skip-sop patterns.•The modelis proposed to precisely formulate the cost under the different OD pairs.•Use the genetic algorithm, and show its effectiveness on the real world instance. This paper focuses on how to minimize the total passeng...

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Veröffentlicht in:Transportation research interdisciplinary perspectives Jg. 9; S. 100309
Hauptverfasser: Zhao, Junru, Ye, Mao, Yang, Zhiqiang, Xing, Zongyi, Zhang, ZiHan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.03.2021
Elsevier
Schlagworte:
Nonlinear mixed integer programming
Operation optimization
Skip-stop pattern
Urban rail transit
Nonlinear mixed integer programming
Urban rail transit
Operation optimization
Skip-stop pattern
ISSN:2590-1982, 2590-1982
Online-Zugang:Volltext
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Zusammenfassung:•Focus on minimizing the total travel time cost by adjusting skip-sop patterns.•The modelis proposed to precisely formulate the cost under the different OD pairs.•Use the genetic algorithm, and show its effectiveness on the real world instance. This paper focuses on how to minimize the total passenger travel time cost by computing and adjusting skip-sop patterns with given time-varying origin-to-destination passenger demand matrices. A bi-objective nonlinear integer programming model with linear constraints is proposed to precisely formulate the total travel time cost and operating cost under minute-dependent demand from the different origin–destination pairs. The proposed model is implemented by using the genetic algorithm with the idea point optimization solvers, and we show its effectiveness on the real world instance of Guangzhou Metro Line 8.
ISSN:2590-1982
2590-1982
DOI:10.1016/j.trip.2021.100309