Multistage stochastic programming model for optimizing allocation of running time supplements

Takayuki Shiina, Susumu Morito, Jun Imaizumi

    Research output: Contribution to journalArticle

    Abstract

    We consider the allocation of a running time supplement to a railway timetable. Previously, Vekas et al. examined the optimal way to allocate the running time supplement. The uncertain disturbances in a railway were modeled using random variables. In their model, it was assumed that there was an upper limit to the total supplement, but its allocation was not restricted. In this paper, we suggest an improvement to the previous model and present a new stochastic programming model in which there is a constraint on the running time supplement allocated to each trip to minimize the expected delay. Then a solution algorithm to solve the problem is developed. In the previous model, allocation of the running time supplement was biased because it was not allocated to all trips. We balance the amounts of supplements for trips by adding upper and lower bounds. The fluctuations of the supplements for trips become small, and the probability of a delay decreases using our new model. Then the calculation times using the L-shaped algorithm and the former method solving a deterministic equivalent of large-scale problems are compared. It is shown that the large-scale problems can be solved effectively by using the L-shaped method.

    Original languageEnglish
    JournalJournal of Advanced Mechanical Design, Systems and Manufacturing
    Volume10
    Issue number3
    DOIs
    Publication statusPublished - 2016

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    Stochastic programming
    Random variables

    Keywords

    • L-shaped method
    • Multistage stochastic programming
    • Optimization
    • Railway timetable
    • Running time supplement

    ASJC Scopus subject areas

    • Mechanical Engineering
    • Industrial and Manufacturing Engineering

    Cite this

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    title = "Multistage stochastic programming model for optimizing allocation of running time supplements",
    abstract = "We consider the allocation of a running time supplement to a railway timetable. Previously, Vekas et al. examined the optimal way to allocate the running time supplement. The uncertain disturbances in a railway were modeled using random variables. In their model, it was assumed that there was an upper limit to the total supplement, but its allocation was not restricted. In this paper, we suggest an improvement to the previous model and present a new stochastic programming model in which there is a constraint on the running time supplement allocated to each trip to minimize the expected delay. Then a solution algorithm to solve the problem is developed. In the previous model, allocation of the running time supplement was biased because it was not allocated to all trips. We balance the amounts of supplements for trips by adding upper and lower bounds. The fluctuations of the supplements for trips become small, and the probability of a delay decreases using our new model. Then the calculation times using the L-shaped algorithm and the former method solving a deterministic equivalent of large-scale problems are compared. It is shown that the large-scale problems can be solved effectively by using the L-shaped method.",
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    AU - Morito, Susumu

    AU - Imaizumi, Jun

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    N2 - We consider the allocation of a running time supplement to a railway timetable. Previously, Vekas et al. examined the optimal way to allocate the running time supplement. The uncertain disturbances in a railway were modeled using random variables. In their model, it was assumed that there was an upper limit to the total supplement, but its allocation was not restricted. In this paper, we suggest an improvement to the previous model and present a new stochastic programming model in which there is a constraint on the running time supplement allocated to each trip to minimize the expected delay. Then a solution algorithm to solve the problem is developed. In the previous model, allocation of the running time supplement was biased because it was not allocated to all trips. We balance the amounts of supplements for trips by adding upper and lower bounds. The fluctuations of the supplements for trips become small, and the probability of a delay decreases using our new model. Then the calculation times using the L-shaped algorithm and the former method solving a deterministic equivalent of large-scale problems are compared. It is shown that the large-scale problems can be solved effectively by using the L-shaped method.

    AB - We consider the allocation of a running time supplement to a railway timetable. Previously, Vekas et al. examined the optimal way to allocate the running time supplement. The uncertain disturbances in a railway were modeled using random variables. In their model, it was assumed that there was an upper limit to the total supplement, but its allocation was not restricted. In this paper, we suggest an improvement to the previous model and present a new stochastic programming model in which there is a constraint on the running time supplement allocated to each trip to minimize the expected delay. Then a solution algorithm to solve the problem is developed. In the previous model, allocation of the running time supplement was biased because it was not allocated to all trips. We balance the amounts of supplements for trips by adding upper and lower bounds. The fluctuations of the supplements for trips become small, and the probability of a delay decreases using our new model. Then the calculation times using the L-shaped algorithm and the former method solving a deterministic equivalent of large-scale problems are compared. It is shown that the large-scale problems can be solved effectively by using the L-shaped method.

    KW - L-shaped method

    KW - Multistage stochastic programming

    KW - Optimization

    KW - Railway timetable

    KW - Running time supplement

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