Abstract:Passengers on metro platforms can board a train only when the train has surplus capacity and the dwell time is sufficient, while the latter condition is omitted in previous studies. Taking into account the impacts of train capacity and dwell time on passengers boarding, this study develops a model on optimizing metro timetable to reduce passenger travel time and metro operating cost, through regulating trains' inter-station run-time, dwell time and headway. The NSGA-II algorithm is employed to obtain the near-… Show more
“…There is a large amount of literature on the train timetable scheduling problem, which considers different objectives, including passenger waiting time [2], [3], [4], travel time [5], [6], energy consumption [7], [8], [9], operating costs [10], [11], robustness [12], and network accessibility [13], [14], [15]. From the perspective of the last-train scheduling problem, it is different from the non-last train in terms of research purposes and methods.…”
Section: Literature Reviewmentioning
confidence: 99%
“…To ensure the safety of train operation, headway limitation is set for the last and the penultimate trains on all lines, as in (11) and (12). In addition, the rescheduled departure time of the last train at the origin station is determined by headway, as in (13).…”
Section: ) Departure and Arrival Timementioning
confidence: 99%
“…The initial population in which the adjustment factors meet the upper and lower restrictions is determined at random, and the generated chromosomes must satisfy formulas (11) and (12) in the model to ensure that they are feasible for reproduction. Once the chromosomes do not satisfy the boundary conditions, they need to be adjusted using formulas (17) and (18).…”
Section: A Initializationmentioning
confidence: 99%
“…Finally, the offspring population is generated by a series of selection, crossover, and mutation operations, which must satisfy formula (5) or (6) and formulas (11) and (12).…”
Section: Selection Crossover and Mutationmentioning
In urban metro systems, train delays make planned timetables uncoordinated, especially during the end-of-service period. Therefore, this study focuses on the timetable rescheduling problem to improve network accessibility. A multi-objective programming model is first proposed to optimize the headway between the last and penultimate train and station dwell time. Minimization of the passenger transfer waiting time for all origin-destination (OD) pairs is meaningful to improve passenger transport efficiency, and a penalty time is used instead of the transfer waiting time of inaccessible passengers, which is important to decrease inaccessible passenger volume. On the other hand, minimization of the total last-train dwell time for all lines is beneficial for decreasing the operating costs for metro operation companies. Then, the adaptive non-dominated sorting genetic algorithm-II (ANSGA-II) is combined with a label setting method to obtain the Pareto optimal solutions. Finally, the Nanjing metro network with randomly-designed delay scenarios is adopted to verify the effectiveness of the proposed rescheduling model and solution algorithm. The results show that this model can yield rescheduling schemes to address the different sudden delay events, resulting in a significant decrease in passenger transfer waiting time and last-train dwell time, thereby improving the network accessibility.INDEX TERMS Adaptive non-dominated sorting genetic algorithm-II, delay management, label setting method, last train, network accessibility.
“…There is a large amount of literature on the train timetable scheduling problem, which considers different objectives, including passenger waiting time [2], [3], [4], travel time [5], [6], energy consumption [7], [8], [9], operating costs [10], [11], robustness [12], and network accessibility [13], [14], [15]. From the perspective of the last-train scheduling problem, it is different from the non-last train in terms of research purposes and methods.…”
Section: Literature Reviewmentioning
confidence: 99%
“…To ensure the safety of train operation, headway limitation is set for the last and the penultimate trains on all lines, as in (11) and (12). In addition, the rescheduled departure time of the last train at the origin station is determined by headway, as in (13).…”
Section: ) Departure and Arrival Timementioning
confidence: 99%
“…The initial population in which the adjustment factors meet the upper and lower restrictions is determined at random, and the generated chromosomes must satisfy formulas (11) and (12) in the model to ensure that they are feasible for reproduction. Once the chromosomes do not satisfy the boundary conditions, they need to be adjusted using formulas (17) and (18).…”
Section: A Initializationmentioning
confidence: 99%
“…Finally, the offspring population is generated by a series of selection, crossover, and mutation operations, which must satisfy formula (5) or (6) and formulas (11) and (12).…”
Section: Selection Crossover and Mutationmentioning
In urban metro systems, train delays make planned timetables uncoordinated, especially during the end-of-service period. Therefore, this study focuses on the timetable rescheduling problem to improve network accessibility. A multi-objective programming model is first proposed to optimize the headway between the last and penultimate train and station dwell time. Minimization of the passenger transfer waiting time for all origin-destination (OD) pairs is meaningful to improve passenger transport efficiency, and a penalty time is used instead of the transfer waiting time of inaccessible passengers, which is important to decrease inaccessible passenger volume. On the other hand, minimization of the total last-train dwell time for all lines is beneficial for decreasing the operating costs for metro operation companies. Then, the adaptive non-dominated sorting genetic algorithm-II (ANSGA-II) is combined with a label setting method to obtain the Pareto optimal solutions. Finally, the Nanjing metro network with randomly-designed delay scenarios is adopted to verify the effectiveness of the proposed rescheduling model and solution algorithm. The results show that this model can yield rescheduling schemes to address the different sudden delay events, resulting in a significant decrease in passenger transfer waiting time and last-train dwell time, thereby improving the network accessibility.INDEX TERMS Adaptive non-dominated sorting genetic algorithm-II, delay management, label setting method, last train, network accessibility.
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