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Journal of ZheJiang University (Engineering Science)  2024, Vol. 58 Issue (10): 2162-2170    DOI: 10.3785/j.issn.1008-973X.2024.10.020
    
Feeder bus route optimization of multiple subway stations considering station transfer
Hao ZHENG(),Yi CAO*(),Shan WANG
School of Traffic and Transportation Engineering, Dalian Jiaotong University, Dalian 116028, China
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Abstract  

The optimization of feeder bus routes was studied to realize the effective connection between bus and subway and improve the transfer efficiency of the bus system. A two-layer programming model was established, considering the origin-destination (OD) demand of passenger flow and the transfer characteristics between multiple subway stations and bus stations. The objective function of the upper layer model aimed to minimize the sum of bus operating cost and passenger travel cost, and the integrity of the route and the rationality of the route were considered as two constraints. The lower layer model was a passenger flow allocation model, which constructed constraint conditions based on the line capacity and the station transfer. An elite retention strategy was introduced, and a model-solving algorithm was designed by combining the neighborhood search algorithm with the genetic algorithm. The case analysis indicated that the minimum error of the designed algorithm was 1.6%, and the algorithm efficiency improved significantly. After the optimization of the bus route network, the bus passenger capacity increased by 29%, and the per capita travel cost decreased by 13%. Experimental results show that the proposed model based on the principle of system optimization optimizes the bus stops around multiple subway stations. The optimization scheme has obvious advantages in improving the load factor, reducing the per capita travel cost and improving the transfer efficiency of the bus system.



Key wordsroute optimization      improved genetic algorithm      neighborhood search      feeder bus      station transfer      global optimization     
Received: 14 August 2023      Published: 27 September 2024
CLC:  U 491.2  
Fund:  辽宁省社会科学规划基金资助项目(L22BSH003).
Corresponding Authors: Yi CAO     E-mail: zhenghao9910@163.com;caoyi820619@aliyun.com
Cite this article:

Hao ZHENG,Yi CAO,Shan WANG. Feeder bus route optimization of multiple subway stations considering station transfer. Journal of ZheJiang University (Engineering Science), 2024, 58(10): 2162-2170.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2024.10.020     OR     https://www.zjujournals.com/eng/Y2024/V58/I10/2162


考虑站点换乘的地铁多车站接运公交线路优化

为了实现公交与地铁的有效接驳,提高公交系统接运效率,开展接运公交线路优化研究. 考虑多个地铁站与公交站间客流的起点?终点(OD)需求与换乘特性,建立双层规划模型. 上层模型的目标函数旨在使公交运营成本及乘客出行成本之和最小化,约束条件考虑线路的完整性、路径的合理性;下层模型为客流分配模型,以线路容量、站点换乘构建约束条件. 引入精英保留策略,将邻域搜索算法与遗传算法组合,设计模型求解算法. 案例分析结果表明,所设计算法的最小误差为1.6%,算法效率显著提升;与原公交线网相比,优化后公交载客量提升29%,人均出行成本降低13%. 实验结果表明,所建模型基于系统最优原则,能够对多个地铁站周边的公交站进行统筹优化;优化方案在提升载客率、降低人均出行成本与提高公交系统接运效率方面优势明显.


关键词: 路线优化,  改进遗传算法,  邻域搜索,  接运公交,  站点换乘,  全局优化 
Fig.1 Diagram of feeder bus route model
Fig.2 Diagram of travel time
Fig.3 Diagram of multiple transfers penalty
Fig.4 Diagram of rationality of feeder route
Fig.5 Diagram of capacity constraints of feeder route
Fig.6 Flow chart of optimization model for feeder bus routes
Fig.7 Distribution of Dalian metro line 1 and nearby bus stops
Fig.8 Relationship between iteration times and total system cost
Fig.9 Diagram of optimization results of feeder route
线路优化线路
改进遗传算法枚举法
14-5-6-1-16-22-254-5-10-1-16-11
29-10-1-7-8-11-239-14-15-1-6-7-8
313-14-15-2-1718-12-13-20-2-21-23
418-12-19-20-2-21-2426-19-2-17-25-24-22
526-29-3-28-30-2729-3-28-30-27
Tab.1 Optimization results of feeder route
名称运行方案top/scz/元?/%
改进遗传算法14220 716.97.6
23820 940.32.7
34321 935.21.6
枚举法162920 386.1
Tab.2 Performance comparison of different algorithms
线路线路编号cb/元q/人cp/元$ {\overline c_{\mathrm{p}}} $/元
优化线路既有公交优化线路既有公交优化线路既有公交优化线路既有公交优化线路既有公交
14-5-6-1-16-22-255-6-7-8-11-1-106109.14857.479354714607.813041.04.14.7
29-10-1-7-8-11-2318-20-2-21-24-25646593
313-14-15-2-176-1-15-2-20-19-26924652
418-12-19-20-2-21-249-13-14-20596414
526-29-3-28-30-2717-22-24-27-30604554
Tab.3 Bus operation and passenger travel costs before and after bus route network optimization
Fig.10 System-optimal modeling solutions
Fig.11 Diagram of station transfer
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