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Innovative Bike-Sharing in China: Solving Faulty Bike-Sharing Recycling Problem

机译:中国创新的共享单车:解决错误的共享单车回收问题

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In China, based on the mobile Internet technology and global positioning system (GPS), innovative bike-sharing is different from traditional bike-sharing system with docking station, for its flexibility and convenience. However, innovative bike-sharing system faces operational challenges, especially in faulty bike-sharing recycling (FBSR) problem. In this paper, a framework is designed based on the optimization method to solve the FBSR problem so that it can minimize the total recycling costs by taking the route optimization and loading capacity ratio as constraints. The FBSR method combines the K-means method for clustering faulty bike-sharing with planning recycling route for operational decisions. Moreover, CPLEX solver is used to obtain the desired result of the FBSR model. Finally, a case study based on a certain area in Beijing, China, is used to verify the validity and applicability of the model. The results show that the value of loading capacity ratio and the number of clustering points greatly affect the results of FBSR problem. Four vehicles are designated to execute FBSR tasks required by different clustering points. This study is of considerable significance for the bike-sharing promotion in the last-mile situation to the real problems arising in the initial period.
机译:在中国,基于移动互联网技术和全球定位系统(GPS),创新的自行车共享与传统的带有扩展坞的自行车共享系统不同,其灵活性和便利性。但是,创新的自行车共享系统面临运营挑战,尤其是在错误的自行车共享回收(FBSR)问题中。本文设计了一种基于优化方法的框架来解决FBSR问题,从而以路线优化和承载能力比为约束条件,可以最大程度地降低总回收成本。 FBSR方法将K-means方法与错误的自行车共享聚类在一起,并规划了回收路线以制定运营决策。此外,CPLEX求解器用于获得FBSR模型的所需结果。最后,以中国北京某地区为例,验证了该模型的有效性和适用性。结果表明,承载力比的值和聚类点的数量对FBSR问题的结果有很大的影响。指定了四辆车来执行不同聚类点所需的FBSR任务。这项研究对于在最后一英里的情况下促进自行车共享对最初阶段出现的实际问题具有重要意义。

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