A static bike repositioning model in a hub-and-spoke network framework

Di Huang, Xinyuan Chen, Zhiyuan Liu, Cheng Lyu, Shuaian Wang and Xuewu Chen

Transportation Research Part E: Logistics and Transportation Review, 2020, vol. 141, issue C

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; Random forests; Hub-and-spoke network framework; Hub-first-route-second (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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DOI: 10.1016/j.tre.2020.102031

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