Operating cost and quality of service optimization for multi-vehicle-type timetabling for urban bus systems

Peña, David; Tchernykh, Andrei; Nesmachnow, Sergio; Массобрио, Рензо; Feoktistov, Alexander; Bychkov, I. V.; Радченко, Глеб; Drozdov, Alexander Yu.; Garichev, Sergey

doi:10.1016/j.jpdc.2018.01.009

Cited by 24 publications

(12 citation statements)

References 22 publications

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“…e vehicle and crew scheduling problem in bus systems is of practical importance because efficient schedules can reduce operational costs and increase the capacity of transit services [55]. Related studies can be traced back to the 1940s when some scholars in developed countries introduced a series of approaches to maximize the scheduling profit [56,57]. Notably, in addition to minimizing the internal and external operating costs and synchronizing departure times, previous studies focused on the following aspects of timetable systems.…”

Section: Vehicle and Crew Schedulingmentioning

confidence: 99%

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

Gao

Zheng

et al. 2021

Discrete Dynamics in Nature and Society

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How to meet the daily demand for resident transport while limiting the transmission of infectious diseases is a problem of social responsibility of urban transport systems during major public health emergencies. Considering the novel coronavirus pneumonia epidemic (COVID-19), a bus timetable system based on the “if early, wait, and if late, leave soon” strategy is proposed. Based on public transport vehicle constraints in this system, the concept of reliability is introduced to evaluate public transport timetable systems, and a model based on an event tree is built to calculate the failure rate of urban bus timetables. Then, the public transport situation in Yixing city is used as an example to perform confirmatory analysis, and the fluctuations in the reliability of the bus timetable during the novel coronavirus pneumonia epidemic are discussed. The research results show that the method proposed in this paper can obtain the overall failure rate of urban bus timetable by traversing the calculation of each round-trip interval and achieve an accurate evaluation of the reliability of bus timetables. During the early, middle, and more recent stages of the COVID-19 outbreak, the failure rate of bus timetables in Yixing city initially decreased and then increased. In the early stage of the outbreak, the failure rate of the Yixing bus timetable was 7.8142. However, the failure rate decreased to 4.3306 and 5.0160 in the middle and late stages of the epidemic, respectively. In other words, the failure rate of the public transport network in the middle and late stages decreased by 44.58% and 35.81%, respectively, compared with that in the early stage. Thus, during major health emergencies, such as the novel coronavirus pneumonia outbreak, the reliability of the urban bus timetable system can be improved by at least 35%, and cross-infection at bus stations can be prevented. The research results verify the feasibility and reliability of the implementation of bus timetabling strategies during major health emergencies.

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Section: Vehicle and Crew Schedulingmentioning

confidence: 99%

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

Gao

Zheng

et al. 2021

Discrete Dynamics in Nature and Society

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“…The quality and diversity of the optimal solution set at convergence are guaranteed. Its excellent optimization performance has led to its application in many fields [46][47][48]. Thus, MOCGA is chosen to optimize the multiobjective model for emergency resource allocation to provide comprehensive and valuable schemes.…”

Section: Multiobjective Cellular Genetic Algorithmmentioning

confidence: 99%

Multiobjective Emergency Resource Allocation under the Natural Disaster Chain with Path Planning

Wang

Xie

Liu

et al. 2022

IJERPH

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Public safety and health cannot be secured without the comprehensive recognition of characteristics and reliable emergency response schemes under the disaster chain. Distinct from emergency resource allocation that focuses primarily on a single disaster, dynamic response, periodic supply, and assisted decision-making are necessary. Therefore, we propose a multiobjective emergency resource allocation model considering uncertainty under the natural disaster chain. Resource allocation was creatively combined with path planning through the proposed multiobjective cellular genetic algorithm (MOCGA) and the improved A* algorithm with avoidance of unexpected road elements. Furthermore, timeliness, efficiency, and fairness in actual rescue were optimized by MOCGA. The visualization of emergency trips and intelligent avoidance of risk areas were achieved by the improved A* algorithm. The effects of logistics performance, coupling of disaster factors, and government regulation on emergency resource allocation were discussed based on different disaster chain scenarios. The results show that disruption in infrastructure support, cascading effect of disasters, and time urgency are additional environmental challenges. The proposed model and algorithm work in obtaining the optimal solution for potential regional coordination and resilient supply, with a 22.2% increase in the total supply rate. Cooperative allocation complemented by political regulation can be a positive action for successfully responding to disaster chains.

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“…presented a bi-objective optimization model for a feeder bus line to minimize operating costs and passengers waiting times with consideration of three different types of buses and proposed a decomposition heuristic algorithm to address the multiple vehicle-types scheduling problem [18]. Peña et al (2019) presented a timetable optimization method based on a multi-objective cellular genetic algorithm, with the aim of optimizing a quality of service and transport operating costs under multiple vehicle-type problems [19]. Gkiotsalitis and Alesiani (2019) developed a robust timetable by applying a bus movement mathematical model that combines the uncertainty of travel times and passenger demand to minimize the possible loss at worst-case scenarios under considering the travel times and passenger demand uncertainty [20].…”

Section: Related Workmentioning

confidence: 99%

Optimal Electric Bus Scheduling Based on the Combination of All-Stop and Short-Turning Strategies

2021

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The emission of greenhouse gases from public transportation has aroused extensive public attention in recent years. Electric buses have the advantage of zero emission, which could prevent the further deterioration of environmental problems. Since 2018, the number of electric buses has exceeded that of traditional buses. Thus, it is an inevitable trend for the sustainable development of the automobile industry to replace traditional fuel buses, and developing electric buses is an important measure to relieve traffic congestion. Furthermore, the bus scheduling has a significant impact on passenger travel times and operating costs. It is common that passenger demand at different stops is uneven in a public transportation system. Since applying all-stop scheduling only cannot match the passenger demand of some stops with bus resources, this paper proposes an integrated all-stop and short-turning service for electric buses, reducing the influence of uneven ridership on load factor to enhance transit attractiveness. Simultaneously, considering the time-of-use pricing strategy used by the power sector, the combinational charging strategy of daytime and overnight is proposed to reduce electricity costs. Finally, the branch-and-price algorithm is adopted to solve this problem. Compared with all-stop scheduling, the results demonstrate a reduction of 13.5% in total time cost under the combinational scheduling.

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Operating cost and quality of service optimization for multi-vehicle-type timetabling for urban bus systems

Cited by 24 publications

References 22 publications

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

Multiobjective Emergency Resource Allocation under the Natural Disaster Chain with Path Planning

Optimal Electric Bus Scheduling Based on the Combination of All-Stop and Short-Turning Strategies

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