Customized Bus Route Vehicle Schedule Method Considering Travel Time Windows

PDF Full Text Download(891 KB)

China Journal of Highway and Transport ›› 2018, Vol. 31 ›› Issue (5) : 143-150.

WANG Jian¹, CAO Yang¹, WANG Yun-hao²

Author information +

History +

Abstract

To improve the operational efficiency of customized bus systems, the schedule method of buses for multiple customized routes was studied considering the time windows of passengers. The merging method for passenger travel stops was considered firstly. The late or early arrivals of customized buses at stops were converted to equivalent bus travel distances. Taking the minimum total travel distance of multiple buses as the objective, a customized bus schedule model was developed based on the passenger stop constraint, bus capacity constraint, and passenger travel time windows. The impacts of passenger travel origin and destination on the model solution were analyzed. By proposing dummy origin stops, the scheduling problem of multiple buses was converted to a multiple traveling salesman problem. A greedy algorithm was designed based on the backward inference principle to obtain a feasible solution of the optimization model. Then based on genetic algorithm, a natural number coding mechanism was then adopted and each stop was set as a gene. The solution to the corresponding problem of chromosomes is lined according to the order of access. The flow of the greedy algorithm and genetic algorithm was given. Finally, a customized bus route was taken as an example to explain the model development process and the solution process. The results show that the developed model in this paper can output reasonable multiple customized bus routes as a schedule plan. It not only outputs the through stops and travel distance, but also the punctuality rate at each stop and the equivalent travel distance due to early or late arrivals. As for the solution quality, compared with the feasible solution, the relative optimal solution can decrease the comprehensive travel distance by 10.4%. The solution time of the model is 30.3 s, which can satisfy the real-time requirements of bus companies.

Key words

traffic engineering / customized bus / greedy algorithm / vehicle schedule / genetic algorithm / travel distance / time window

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

WANG Jian, CAO Yang, WANG Yun-hao. Customized Bus Route Vehicle Schedule Method Considering Travel Time Windows[J]. China Journal of Highway and Transport, 2018, 31(5): 143-150

References

[1] 魏华,马荣国,吕斌,等.基于信息熵的公交优先线控系统相位差优化模型[J].中国公路学报,2014,27(5):158-163.WEI Hua, MA Rong-guo, LU Bin, et al. Offset Optimization of Bus Priority Arterial Traffic Control Based on Information Entropy[J]. China Journal of Highway and Transport, 2014, 27(5):158-163.
[2] YAN Y, LIU Z, BIE Y. Performance Evaluation of Bus Routes Using Automatic Vehicle Location Data[J]. Journal of Transportation Engineering, 2016, 142(8):1-12.
[3] TSUBOUCHI K, YAMATO H, HIEKATA K. Innovative On-demand Bus System in Japan[J]. IET Intelligent Transport Systems, 2010, 4(4):270-279.
[4] NEVEN A, BRAEKERS K, DECLERCQ K, et al. Assessing the Impact of Different Policy Decisions on the Resource Requirements of a Demand Responsive Transport System for Persons with Disabilities[J]. Transport Policy, 2015, 44:48-57.
[5] QIU F, LI W, ZHANG J. A Dynamic Station Strategy to Improve the Performance of Flex-route Transit Services[J]. Transportation Research Part C:2014, 48:229-240.
[6] CHANG S K, YU W J. Comparison of Subsidized Fixed and Flexible-route Bus Systems[J]. Transportation Research Record, 1996(1557):15-20.
[7] BROOME K, WORRALL L, FLEMING J, et al. Evaluation of Flexible Route Bus Transport for Older People[J]. Transport Policy, 2012, 21:85-91.
[8] LIU T, CEDER A A. Analysis of a New Public-transport-service Concept:Customized Bus in China[J]. Transport Policy, 2015, 39:63-76.
[9] 杨得婷.定制公交票价制定与运营相关问题研究[D].西安:长安大学,2015.YANG De-ting. The Study on Issues Related Customized City Bus Fare and Operation[D]. Xi'an:Chang'an University, 2015.
[10] 刘冬梅.西安市定制公交运行方案研究[D].西安:长安大学,2014.LIU Dong-mei. The Transit Scheme Research on Customized City Bus Service of Xi'an[D]. Xi'an:Chang'an University, 2014.
[11] 王姣.定制公交行车站点规划与时刻表编制研究[D].北京:北京交通大学,2016.WANG Jiao. Research on Station Planning and Timetable of Customized Bus[D]. Beijing:Beijing Jiaotong University, 2016.
[12] CAO Y, WANG J. The Key Contributing Factors of Customized Shuttle Bus in Rush Hour:A Case Study in Harbin City[J]. Procedia Engineering, 2016, 137:478-486.
[13] BIE Y, GONG X, LIU Z. Time of Day Intervals Partition for Bus Schedule Using GPS Data[J]. Transportation Research Part C, 2015, 60:443-456.
[14] ZHANG J, WANG D Z W, MENG M. Analyzing Customized Bus Service on a Multimodal Travel Corridor:An Analytical Modeling Approach[J]. Journal of Transportation Engineering, Part A:Systems, 2017, 143(11):1-12.
[15] BIE Y, LIU Z, LU L. Optimization of Coordinated Signal Settings for Hook-turn Intersections[J]. Journal of Advanced Transportation, 2016, 50(2):197-213.
[16] BIE Y, WANG D, QI H. Prediction Model of Bus Arrival Time at Signalized Intersection Using GPS Data[J]. Journal of Transportation Engineering, 2012, 138(1):12-20.
[17] CHIEN S I J, DING Y, WEI C. Dynamic Bus Arrival Time Prediction with Artificial Neural Networks[J]. Journal of Transportation Engineering, 2002, 128(5):429-438.
[18] 杨国兴.一种多出发点多旅行商问题到旅行商问题的转换[J].系统工程理论方法应用,1993,2(3):66-68.YANG Guo-xing. A Transformation of the Multidepot Multisalesmem Problem to the Standard Traveling Salesman Problem[J]. Systems Engineering-Theory Methodology Applications, 1993, 2(3):66-68.
[19] 卢厚清,王辉东,黄杰,等.任务均分的多旅行商问题[J].系统工程,2005,23(2):19-21.LU Hou-qing, WANG Hui-dong, HUANG Jie, et al. Dividing into Equal Task of MTSP[J]. Systems Engineering, 2005, 23(2):19-21.
[20] CHANG P C, HUANG W H, TING C J. Dynamic Diversity Control in Genetic Algorithm for Mining Unsearched Solution Space in TSP Problems[J]. Expert Systems with Applications, 2010, 37(3):1863-1878.
[21] LIU F, ZENG G. Study of Genetic Algorithm with Reinforcement Learning to Solve the TSP[J]. Expert Systems with Applications, 2009, 36(3):6995-7001.

PDF Full Text Download(891 KB)

2067

Accesses

Citation

Detail

Sections

Recommended

Abstract
Key words
Cite this article
References

Received	Published
2017-10-04	2018-05-20
Issue Date
2018-06-04

Please choose a citation manager

Content to export

Abstract

Key words

Cite this article

{{custom_sec.title}}

{{custom_sec.title}}

References

{{custom_fnGroup.title_en}}

Footnotes

模态框（Modal）标题

Please choose a citation manager

Content to export

Abstract

Key words

Cite this article

{{custom_sec.title}}

{{custom_sec.title}}

References

{{custom_fnGroup.title_en}}

Footnotes