| Title: | A static bike repositioning model in a hub-and-spoke network framework | Authors: | Huang, D Chen, X Liu, Z Lyu, C Wang, S Chen, X |
Issue Date: | Sep-2020 | Source: | Transportation research. Part E, Logistics and transportation review, Sept. 2020, v. 141, 102031, p. 1-21, https://doi.org/10.1016/j.tre.2020.102031 | Abstract: | This paper addresses a static bike repositioning problem by embedding a short-term demand forecasting process, the Random Forest (RF) model, to account for the demand dynamics in the daytime. To tackle the heterogeneous repositioning fleets, a novel repositioning operation strategy constructed on the hub-and-spoke network framework is proposed. The repositioning optimization model is formulated using mixed-integer programming. An artificial bee colony algorithm, integrated with a commercial solver, is applied to address computational complexity. Experimental results show that the RF can achieve a high forecasting accuracy, and the proposed repositioning strategy can efficiently decrease the users’ dissatisfaction. | Keywords: | Bike repositioning Demand forecasting Hub-and-spoke network framework Hub-first-route-second Random forests |
Publisher: | Pergamon Press | Journal: | Transportation research. Part E, Logistics and transportation review | ISSN: | 1366-5545 | EISSN: | 1878-5794 | DOI: | 10.1016/j.tre.2020.102031 |
| Appears in Collections: | Journal/Magazine Article |
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