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Optimization Model and Algorithm for Dockless Bike-Sharing Systems Considering Unusable Bikes in China

机译:考虑中国不可用自行车的Dockless自行车共享系统的优化模型与算法

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摘要

The damaged dockless shared-bikes are increasingly common in large cities of China, which not only reduce users & x2019; satisfactions but also harm the public environment. It is a merging issue for dockless bike-sharing systems to timely recall unusable bikes and replenish new/usable bikes. This paper addresses a maintenance network for a dockless bike-sharing system within a specific region in which the random demands and returns of shared-bikes are considered and the returned bikes have a certain probability to be unusable. The problem is to jointly determine the numbers of unusable and usable bikes to be recalled and replenished, respectively, and the corresponding routes of maintenance vehicles via the maintenance network. The problem is formulated as a stochastic mixed-integer programming model with the objective to maximize the expected revenue of the maintenance network within a operational period. To resolve the such complicated integration-optimization problem efficiently, the formulated model is decomposed into a multi-location newsvendor subproblem and a multiple vehicle routing subproblem with simultaneous delivery and pick-up. An efficient two-stage heuristics is then proposed, which resolves the two subproblems in the two stages of the algorithm, respectively. The computational results based on an real numerical case and a large number of numerical instances validate the performance of the proposed model and algorithm.
机译:在中国的大城市越来越常见的损坏的停机坪共享自行车,这不仅减少了用户和X2019;满意,但也造成危害公共环境。这是Dockless Bike分享系统的合并问题,以及时回忆不可用的自行车,并补充新的/可用自行车。本文在考虑了一个特定区域内的无需自行车共享系统的维护网络,其中考虑了随机需求和返回的共享自行车,并且返回的自行车具有一定可能是无法使用的概率。问题是共同确定要召回和补充和补充的不可用和可用的自行车的数量,以及通过维护网络的相应维护车辆。该问题被制定为随机混合整数编程模型,目的是在运行期内最大化维护网络的预期收入。为了有效地解决此类复杂的集成优化问题,配制的模型被分解为多个位置新闻官员子发布和多车辆路由子发布,同时传送和接送。然后提出了一种有效的两级启发式,分别解析了算法的两个阶段中的两个子问题。基于真正的数字案例和大量数值实例的计算结果验证了所提出的模型和算法的性能。

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