A worker‐and‐system trade‐off model for rebalancing free‐float bike sharing systems: A mixed rebalancing strategy

Because of imbalanced spatial‐temporal user demands, situations with no available bikes or docks often occur. In order to better response to user demands, many researchers are devoted to rebalancing bike sharing systems (BSS). Existing researches focus primarily on rebalancing BSS by trucks or by workers individually, resulting in two issues: (a) the high cost and massive emissions associated with trucks‐based rebalancing; and (b) the low efficiency associated with workers‐based rebalancing. This paper combines two rebalancing methods together and proposes a mixed rebalancing strategy to tackle the aforementioned issues. This strategy rebalances free‐floating BSS (FBSS) by trucks on the eve of peak hours and by workers during peak hours, in which the worker‐based rebalancing plan is given by a worker‐and‐system trade‐off model which simultaneously considers the impact of workers' costs and real‐time inventory of stations. A case study is conducted on two scenarios of the Beijing Mobike dataset: the Beigongdaximen subway station and the Jinyijiayuan residential area. The results show that our mixed rebalancing strategy can effectively rebalance FBSS by improving the following four indices: rebalancing cost, usage rate of shared bikes and docks, survival time of stations, and demand satisfaction. We introduce a worker‐and‐system trade‐off model to determine the rebalancing plan. The results show that the WST‐based mixed rebalancing strategy can effectively rebalance FBSS by improving the following four indices: rebalancing cost, usage rate of shared bikes and docks, survival time of stations, and demand satisfaction.