数学理论与应用 ›› 2020, Vol. 40 ›› Issue (4): 118-127.

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基于排队论的机场上客区系统效益优化研究

李美玉1,李倩2,张天宇3,王浩华2*   

  1. 1.海南大学 经济学院 金融学系,海南 海口 570228

    2.海南大学 理学院 数学系,海南 海口 570228

    3.海南大学 信息与通讯工程学院电子信息与工程系, 海南 海口 570228

  • 出版日期:2020-12-30 发布日期:2021-06-15
  • 通讯作者: 王浩华(1981- ), 男, 教授,E-mail:huazi8112@hainanu.edu.cn.
  • 基金资助:

    海南省自然科学基金(120RC451),

    国家自然科学基金(1176102511901114),

    广东省教育厅青年创新人才类(2017KQNCX081)

    广州市科技创新一般项目(201904010010)

    中山大学广东省计算科学重点实验室开放课题基金资助(2018001)

    海南省研究生创新科研课题项目(Hys2019-59

Study on System Benefit Optimization of Airport Pick-up Area Based on Queuing Theory

  • Online:2020-12-30 Published:2021-06-15

摘要:

以实现机场出租车上客区乘车效率最高为目标,充分考虑乘客、出租车司机的时间成本以及上车点的建设成本,本文运用排队论的思想来研究机场出租车上客区的最优上车点个数。以北京首都机场为例,建立了出租车与乘客的双端排队模型,分别求解出使排队长度达到最短的上车点个数,进而实现乘车效率最高。此外,还以总成本最小为优化目标对排队模型进行验证与优化,结论表明设定的上车点个数不仅能使乘车效率达到最高,同时也可做到总成本最低。最后通过设置出租车司机与乘客的满意度权值并分别赋予两排队模型,得出最优上车点个数为7个。

关键词:

机场出租车  , 乘车效率  , 上车点个数  , 排队论  , 成本优化

Abstract:  This paper aims to achieve the highest efficiency of boarding in the airport taxi boarding area, and takes into full consideration the time cost of passengers and taxi drivers as well as the construction cost of boarding points, and applies the idea of Queuing Theory to study the optimal number of boarding points in the airport taxi boarding area. Taking Beijing capital airport as an example, this paper establishes a double-end queuing model for taxi and passenger, and respectively solves the number of boarding points that make the queue length reach the shortest, so as to achieve the highest efficiency. In addition, this paper also took the minimum total cost as the optimization objective to verify and optimize the queuing model, and found that the set number of boarding points could not only achieve the highest efficiency, but also achieve the lowest total cost. Finally, by setting the satisfaction weights of taxi drivers and passengers and assigning them to two queuing models, the optimal number of boarding points was obtained to be 7.

Key words:

airport taxi, driving efficiency, number of boarding points, Queuing Theory, cost optimization