基于凸最小成本流的网约车市场车辆再分配
Vehicle Redistribution in Ride-Sourcing Markets using Convex Minimum Cost Flows
摘要：
乘车外包平台经常面临其运营道路网络中各地区乘车需求和供应的不平衡。因此，动态定价方法已被用来通过激增价格乘数来调解这些需求不对称，从而激励更多的司机参与市场。然而，自动驾驶汽车的预期商业化可能会将当前的乘车外包平台转变为车队运营商。人类驾驶员的缺乏促进了对空车辆管理的需求，以解决任何车辆供应不足的问题。在研究中已经提出了使用整数规划和需求预测模型的主动再分配来解决这个问题。然而，现有模型的一个缺点是，它们忽略了市场结构和潜在的客户选择行为。因此，目前的模式没有捕捉到再分配的真正价值。为了解决这个问题，我们制定的车辆再分配问题作为一个非线性的最小成本流问题，占的关系，提供和需求的游乐设施，通过假设客户离散选择模型和市场结构。我们证明了这个模型可以有一个凸域，我们引入了一个边缘分裂算法来解决车辆再分配的转换凸最小费用流问题。通过模拟测试我们的模型，我们表明，我们的重新分配算法可以减少等待时间超过50%，增加利润高达10%，车辆里程增加不到20%。我们的研究结果表明，再分配的价值取决于本地化的市场结构和客户行为。
英文摘要：
Ride-sourcing platforms often face imbalances in the demand and supply of rides across areas in their operating road-networks. As such, dynamic pricing methods have been used to mediate these demand asymmetries through surge price multipliers, thus incentivising higher driver participation in the market. However, the anticipated commercialisation of autonomous vehicles could transform the current ride-sourcing platforms to fleet operators. The absence of human drivers fosters the need for empty vehicle management to address any vehicle supply deficiencies. Proactive redistribution using integer programming and demand predictive models have been proposed in research to address this problem. A shortcoming of existing models, however, is that they ignore the market structure and underlying customer choice behaviour. As such, current models do not capture the real value of redistribution. To resolve this, we formulate the vehicle redistribution problem as a non-linear minimum cost flow problem which accounts for the relationship of supply and demand of rides, by assuming a customer discrete choice model and a market structure. We demonstrate that this model can have a convex domain, and we introduce an edge splitting algorithm to solve a transformed convex minimum cost flow problem for vehicle redistribution. By testing our model using simulation, we show that our redistribution algorithm can decrease wait times by more than 50%, increase profit up to 10% with less than 20% increase in vehicle mileage. Our findings outline that the value of redistribution is contingent on localised market structure and customer behaviour.
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