Equity-oriented integrated optimization of train timetable and stop plans for suburban railways system. (November 2022)

• Record Type: Journal Article
• Authors: Shao, Juan; Xu, Yan; Sun, Lishan; Kong, Dewen; Lu, Huabo
• Is Part Of: Computers & industrial engineering. Volume 173(2022)
• Publication Date: 2022-11
• Subjects: Suburban railway -- Integrated optimization -- Train timetable -- Train stop plan -- Equity performance; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108721
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Quantitative evaluation the equity issue in train scheduling is developed. An integrated model to optimize the train stop plan and timetable is formulated. An improved extended adaptive large neighborhood search approach is developed. The model is tested for case studies of Chinese Shanghai-Jinshan suburban railway. The relationship between fairness, efficiency, and cost is analyzed. Abstract: 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 multi-objective 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.