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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Vydané v:Transportation research interdisciplinary perspectives Ročník 9; s. 100309
Hlavní autori: Zhao, Junru, Ye, Mao, Yang, Zhiqiang, Xing, Zongyi, Zhang, ZiHan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.03.2021
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Abstract •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.
AbstractList •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.
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.
ArticleNumber 100309
Author Xing, Zongyi
Zhao, Junru
Yang, Zhiqiang
Ye, Mao
Zhang, ZiHan
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10.1016/j.ejor.2013.11.007
10.1016/j.endm.2018.07.028
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Keywords Nonlinear mixed integer programming
Urban rail transit
Operation optimization
Skip-stop pattern
Language English
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Snippet •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...
This paper focuses on how to minimize the total passenger travel time cost by computing and adjusting skip-sop patterns with given time-varying...
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StartPage 100309
SubjectTerms Nonlinear mixed integer programming
Operation optimization
Skip-stop pattern
Urban rail transit
Title 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
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