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- W3134604562 abstract "Following the bike-sharing system, the shared e-bike becomes increasingly popular due to the advantage in speed, trip distance, and so forth. However, limited research has investigated the impact of the introduction of shared e-bikes on the existing bike-sharing systems. This paper aims to study the effect of shared e-bikes on the traditional bike-sharing system and determine the optimal fleet deployment strategy under a bimodal transportation system. A stochastic multiperiod optimisation model is formulated to capture the demand uncertainty of travelers. The branch-and-bound algorithm is applied to solve problem. A 15-station numerical example is applied to examine the validity of the model and the effectiveness of the solution algorithm. The performance of integrated e-bike and bike-sharing system has been compared with the traditional bike-sharing system. The impacts of the charging efficiency, fleet size, and pricing strategy of e-bike-sharing system on the traditional bike-sharing system have been examined." @default.
- W3134604562 created "2021-03-15" @default.
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- W3134604562 date "2021-02-26" @default.
- W3134604562 modified "2023-10-13" @default.
- W3134604562 title "Optimal Fleet Deployment Strategy: Model the Effect of Shared E-Bikes on Bike-Sharing System" @default.
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- W3134604562 doi "https://doi.org/10.1155/2021/6678637" @default.
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