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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68118


    Title: 隨機需求之自行車共享系統中再平衡和車輛途程問題;Rebalancing and Vehicle Routing for Bike Sharing Systems with Stochastic Demands
    Authors: 薛喨;Hsueh,Liang
    Contributors: 工業管理研究所
    Keywords: 自行車共享系統;隨機需求;車輛途程;行產生法;Bike sharing systems;Stochastic Demands;Vehicle Routing;Column Generation
    Date: 2015-07-29
    Issue Date: 2015-09-23 10:45:10 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 近年來,公共自行車系統已成為都市民眾生活的一部分,不僅增加城市形象更成為疏通交通的工具,雖然公共自行車站不需要人力協助租借服務,但仍然具有定期維修與車輛調度之需求,和需要人力維持服務品質。
    當城市仰賴公共自行車租賃系統,則需要持續維持高服務水準與服務品質,此時如何有效提升服務率便成為十分重要的問題。公共自行車租賃服務與商品出售不同,因為交通網路始終維持固定數量的自行車,搬運車補貨必定來自其他自行車站,且過多與過少的配置都會形成浪費。因此,有必要探討如何有效滿足補貨需求以降低成本。
    本研究探討在多台運補車同時進行運補,但每個車站只能造訪一次的情況。首先,我們先設計每站的服務水準並計算需要運補的自行車數量。然後我們提出一個基於行產生法的演算法來找尋最佳的解決方案。
    ;In recent years public bike systems have become part of the life of urban residents, not only increase the city’s image and become a tool to clear traffic. Although public bike station does not need human to assist rental service, it still needs regular maintenance schedule of the vehicle, and manpower to maintain the quality of service.
    When the city relies on public bike rental system, we need to continue to maintain a high standard of service and quality of service, at this time, how to effectively improve service rate becomes a very important issue. Public bike rental service is different from the sale of goods, because the transportation network has always been to maintain a fixed number of bikes, vehicle replenish bikes must dome from other bike stations, and too much or too less configuration will cause the cost burden, it is therefore necessary to explore how to meet replenishment requirements and reduce costs.
    In this study, in the case of multiple vehicles and a single visit the station is set. First, we calculate how many bikes should we pickup or delivery based on the service level of each station. Then we proposed an algorithm to solve the routing problem based on Column Generation to find an optimal solution.
    Appears in Collections:[工業管理研究所 ] 博碩士論文

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