4.7 Article

Equity-oriented integrated optimization of train timetable and stop plans for suburban railways system

期刊

COMPUTERS & INDUSTRIAL ENGINEERING
卷 173, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2022.108721

关键词

Suburban railway; Integrated optimization; Train timetable; Train stop plan; Equity performance

资金

  1. National Natural Science Foundation of China
  2. Beijing Municipal Education Commission Science and Technology Program General Project
  3. Beijing Municipal Education Commission Science and Technology Pro- gram General Project
  4. [71901008]
  5. [KM202010005001]
  6. [KM202110005002]

向作者/读者索取更多资源

This paper focuses on improving the system-wide equity performance of the suburban railway system by optimizing the train timetable and stop plan. A novel equation is developed to estimate equity performance, and an integrated optimization model is proposed to minimize total travel time, train running time, and equity performance. Unlike other studies, this paper synchronously optimizes the train timetable and stop plan, expanding the solution space.
In the suburban railway system, when oversaturation occurs in the railway line or the train skips the same station continuously, passengers waiting at different stations may receive a varying share of train resources. As a result, some passengers have to endure a very long waiting time, causing issues of inequity. Thus, this paper focuses on improving the system-wide equity performance through integrated optimization of the train timetable and stop plan while ensuring travel efficiency and cost rationality. As a part of the study, a novel equation to estimate equity performance by considering the difference in passenger travel utility is developed. Then, an integrated optimization model combining the train timetable and stop plan is proposed to minimize total travel time, train running time, and equity performance. Unlike other studies in the literature, this paper does not define any initial set of stopping plans, and synchronously optimizes the train timetable and stops the plan. This facilitates obtaining better solutions by expanding the solution space. Furthermore, it overcomes the NP-hardness of the investigated problem by using the adaptive large-scale neighborhood search (ALNS) algorithm to solve the multiobjective mixed-integer linear programming model. Finally, this paper discusses the original and optimized scheduling indicators of a real-world case based on the Shanghai Jinshan railway and performs a sensitivity analysis on equity weights. The results show that the proposed approach can improve the overall benefits of efficiency, cost, and equity by 23%. Specifically, in terms of equity, the passenger travel utility variance was reduced by 42.8%. This analysis provides essential information to railway managers in formulating the train operation plan.

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