Ride-Hailing Assignment Problem under Waiting Time Uncertainty using Interval-Valued Fuzzy Quadratic

S. Supian, S. Subiyanto, Tubagus Robbi Megantara, Abdul Talib Bon
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Abstract

Ride-hailing is a creative idea created by transportation supported by science and technology. Ride-hailing services can help daily community activities. The issue with ride-hailing is that traffic conditions are unpredictable, implying that waiting times are uncertain. The time passengers spend waiting from when they book a ride service until the driver arrives at the pick-up location is called waiting time. This study suggests a quadratic programming technique for minimizing waiting time while accounting for the unpredictability of pick-up travel time. The interval-valued fuzzy quadratic programming method handles the uncertainty and imprecision of the anticipated journey time. When allocating drivers to pick up passengers, interval-valued fuzzy numbers can provide a more realistic representation of waiting time uncertainty. As a result, the interval-valued fuzzy quadratic programming model can handle the uncertainty in waiting time for ride-hailing assignment problems. The model's performance is evaluated using waiting time and the number of people served. The model's performance is demonstrated numerically using the simulation-based case study. This study shows how to utilize a mathematical method to solve real-world problems with uncertainty and improve user welfare.
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使用区间值模糊二次方解决等待时间不确定条件下的乘车分配问题
打车服务是以科学技术为支撑的交通方式创造出的一种创意。打车服务有助于社区的日常活动。打车服务的问题在于交通状况不可预测,这意味着等待时间不确定。乘客从预订乘车服务到司机到达接送地点的等待时间称为等待时间。本研究提出了一种二次编程技术,在考虑到接送时间不可预测性的同时,最大限度地减少等待时间。区间值模糊二次编程法处理了预期行程时间的不确定性和不精确性。在分配司机接送乘客时,区间值模糊数可以更真实地反映等待时间的不确定性。因此,区间值模糊二次编程模型可以处理乘车分配问题中等待时间的不确定性。利用等待时间和服务人数对模型的性能进行了评估。通过基于模拟的案例研究,对模型的性能进行了数值演示。这项研究展示了如何利用数学方法解决现实世界中存在不确定性的问题,并提高用户福利。
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