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主管单位 中华人民共和国
工业和信息化部
主办单位 哈尔滨工业大学 主编 李隆球 国际刊号ISSN 0367-6234 国内刊号CN 23-1235/T

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引用本文:王鑫,曲昭伟,宋现敏,张明业.城市热点区域出租车停靠站双目标选址优化模型[J].哈尔滨工业大学学报,2020,52(5):106.DOI:10.11918/201909162
WANG Xin,QU Zhaowei,SONG Xianmin,ZHANG Mingye.Bi-objective location optimization model for taxi stands in urban hotspots[J].Journal of Harbin Institute of Technology,2020,52(5):106.DOI:10.11918/201909162
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城市热点区域出租车停靠站双目标选址优化模型
王鑫,曲昭伟,宋现敏,张明业
(吉林大学 交通学院,长春 130022)
摘要:
为确保城市出租车停靠站布局的合理性,改善站点利用率低的现状,提出一种基于GPS轨迹数据的出租车停靠站双目标选址决策方法.在数据背景下,对出租车出行需求量及候选点位置进行估计.考虑乘客出行需求的覆盖率、乘客可接受的最大出行距离、站点及站位的服务能力等影响因素,构建了出租车停靠站空间布局的约束条件.分别从规划者和使用者的角度出发,提出了建设成本最小化和公众满意度最大化的双目标选址优化模型.应用基于遗传算法的宽容分层序列法,对模型进行求解.以成都市春熙路商圈为例,运用所提出的优化方法对该区域的出租车停靠站进行重新选址,并研究不同的乘客期望出行距离对选址问题的影响.结果表明:当乘客的期望出行距离小于300 m时,新的站点布局方案能够以合理的站点数量覆盖区域内的全部出行需求,同时保证乘客的出行满意度处于较高水平,验证了双目标选址模型的有效性.
关键词:  交通工程  出租车停靠站  GPS轨迹数据  双目标优化  遗传算法
DOI:10.11918/201909162
分类号:U491
文献标识码:A
基金项目:吉林省自然科学基金(20180101063JC); 吉林省教育厅“十三五”科学技术项目(JJKH20190153KJ)
Bi-objective location optimization model for taxi stands in urban hotspots
WANG Xin,QU Zhaowei,SONG Xianmin,ZHANG Mingye
(School of Transportation, Jilin University, Changchun 130022, China)
Abstract:
To ensure the rationality of urban taxi stands layout and improve the situation of low utilization rate, a location-decision method of taxi stands based on GPS trajectory data was proposed. The demand for taxi trips and locations of candidate stands were estimated under the background of data. Considering the factors such as the coverage of passenger travel demand, the maximum acceptable distance for passengers, and the service capacity of stand and parking space, the constraint conditions for taxi stands layout were constructed. A bi-objective location optimization model was proposed to minimize construction costs and maximize public satisfaction from the perspectives of planners and users, respectively. The forbearing stratified sequencing method based on genetic algorithm was applied to solve the model. Taking the Chunxi business district of Chengdu as an example, the taxi stands in the area were re-located using the proposed model, and the impact of different expected travel distances of passengers on location decision problem was investigated. Results show that when the expected travel distance of passenger was less than 300 m, the new layout scheme could cover all travel demands in the area with a reasonable number of stands and ensure the passengers’ travel satisfaction at a high level, which verifies the validity of the bi-objective location model.
Key words:  transportation engineering  taxi stand  GPS trajectory data  bi-objective optimization  genetic algorithm

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