基于边界曲线的多因素机场出租车管理系统模型

Multi-factor Airport Taxi Managerial Model Based on Marginal Curve

  • 摘要: 该文基于上海浦东国际机场的相关数据对机场出租车的决策安排等问题建立模型并进行分析。使用多因素决策模型解决司机是否进入蓄车池问题,绘制出蓄车池当前车数边界值与时间的变化曲线。采用“分批定量”规则,建立多目标优化模型,解决了上车点安排问题。以收益标准差最小为目标,解决了短程载客车辆“优先权”问题。用浦东机场航班等数据代入模型可得浦东机场的蓄车池车数边界曲线、最优上车点设置和短程载客车辆的最优时间补贴。从而验证了方法的效果与合理性。

     

    Abstract: In this article, based on the data of Shanghai Pudong International Airport(PVG), a model of decision-making management of airport taxi is created and analyzed. A multi-factor decision model is developed to decide whether drivers get into the taxi storage pool depending on how the cost of waiting compares with the cost of driving back without passengers. We plot the marginal curve of the number of taxis in pool to the time change. For the problem of arrangement of the pick-up locations, a multi-objective optimization model is created with the rule of “certain amounts in turn”. For the priority of short-distance drivers, with the goal of the minimum standard deviation of returns, they can pick up the passengers without waiting. By using the data of PVG into the model, we get the marginal curve of the maximal number of taxis in storage pool to time, the optimal pick-up locations and the optimal time subsidy for short-distance drivers. The effect and rationality of the model are verified.

     

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