合乘:人与包裹合乘出租车的双重服务模式与包裹的松散时间窗口

IF 2.3 4区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Systems Pub Date : 2024-08-14 DOI:10.3390/systems12080302
Shuqi Xue, Qi Zhang, Nirajan Shiwakoti
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引用次数: 0

摘要

(1) 高效利用城市交通资源需要客运和货运系统的整合。目前的研究侧重于动态响应客运和包裹订单,通常是先规划客运路线,然后动态插入包裹请求。然而,与客运严格的时间限制相比,这种方法忽略了包裹交付时间固有的灵活性。(2) 本研究引入了一种提高出租车资源利用率的新方法,提出了一种人员和包裹运输共享模型,即 SARP-LTW(包裹时间窗口宽松的合乘问题)模型。我们的模型考虑了包裹递送的宽松时间窗口,并在每个工作日之前,即在处理乘客请求之前,为每辆出租车初步定义了包裹递送路线。每个出租车工作日开始后,所有出租车将优先处理乘客的动态出行请求,尽量减少这些请求的延迟,唯一的要求是确保所有预先安排的包裹都能送达目的地。(3) 这种双重服务方法旨在优化利润,同时兼顾乘客订单的时间敏感性和包裹交付的灵活性。此外,我们还通过引入蚁群信息更新机制(AC-ALNS)改进了自适应大邻域搜索算法,以高效求解 SARP-LTW。(4) 对著名的所罗门基准实例集的数值分析表明,SARP-LTW 模型在利润率、收入和收入稳定性方面优于 SARP 模型,分别提高了 48%、46% 和 49%。我们提出的方法使出租车公司能够最大限度地提高车辆利用率,减少闲置时间,增加收入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sharing a Ride: A Dual-Service Model of People and Parcels Sharing Taxis with Loose Time Windows of Parcels
(1) Efficient resource utilization in urban transport necessitates the integration of passenger and freight transport systems. Current research focuses on dynamically responding to both passenger and parcel orders, typically by initially planning passenger routes and then dynamically inserting parcel requests. However, this approach overlooks the inherent flexibility in parcel delivery times compared to the stringent time constraints of passenger transport. (2) This study introduces a novel approach to enhance taxi resource utilization by proposing a shared model for people and parcel transport, designated as the SARP-LTW (Sharing a ride problem with loose time windows of parcels) model. Our model accommodates loose time windows for parcel deliveries and initially defines the parcel delivery routes for each taxi before each working day, which was prior to addressing passenger requests. Once the working day of each taxi commences, all taxis will prioritize serving the dynamic passenger travel requests, minimizing the delay for these requests, with the only requirement being to ensure that all pre-scheduled parcels can be delivered to their destinations. (3) This dual-service approach aims to optimize profits while balancing the time-sensitivity of passenger orders against the flexibility in parcel delivery. Furthermore, we improved the adaptive large neighborhood search algorithm by introducing an ant colony information update mechanism (AC-ALNS) to solve the SARP-LTW efficiently. (4) Numerical analysis of the well-known Solomon set of benchmark instances demonstrates that the SARP-LTW model outperforms the SARP model in profit rate, revenue, and revenue stability, with improvements of 48%, 46%, and 49%, respectively. Our proposed approach enables taxi companies to maximize vehicle utilization, reducing idle time and increasing revenue.
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来源期刊
Systems
Systems Decision Sciences-Information Systems and Management
CiteScore
2.80
自引率
15.80%
发文量
204
审稿时长
11 weeks
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