Abstract
Bike sharing systems, as one of the complementary modes for public transit networks, are designed to help travelers in traversing the first/last mile of their trips. Different factors such as accessibility, availability, and fares influence these systems. The availability of bikes at certain times and locations is studied under rebalancing problem. The paper proposes a bottom-up cluster-based model to solve the static rebalancing problem in bike sharing systems. First, the spatial and temporal patterns of bike sharing trips in the network are investigated. Second, a similarity measure based on the trips between stations is defined to discover groups of correlated stations, using a hierarchical agglomerative clustering method. Third, two levels for rebalancing are assumed as intra-clusters and inter-clusters with the aim of keeping the balance of the network at the beginning of days. The intra-cluster level keeps the balance of bike distribution inside each cluster, and the inter-cluster level connects different clusters in order to keep the balance between the clusters. Finally, rebalancing tours are optimized according to the positive or negative balance at both levels of the intra-clusters and inter-clusters using a single objective genetic algorithm. The rebalancing problem is modeled as an optimization problem, which aims to minimize the tour length. The proposed model is implemented in one week of bike sharing trip data set in Chicago, USA. Outcomes of the model are validated for two subsequent weekdays. Analyses show that the proposed model can reduce the length of the rebalancing tour by 30%.
Highlights
Quality of service in bike sharing systems is an important operational problem for authorities
From the operational viewpoint of bike sharing systems, one of the challenges is to keep the balance of bikes which are scattered in an unbalanced way over the stations due to the users’ one-way daily trips
Most of the studies deal with the static rebalancing problem [1,4,5,10,11,14,15,17]
Summary
Quality of service in bike sharing systems is an important operational problem for authorities. In order to keep the quality of service at a certain level, these systems need rebalancing to compensate unbalances in the network. The static rebalancing problem is keeping the balance of all stations in the network at a predetermined level. The process of rebalancing usually is carried out by vehicles. The vehicles start from the deposit (depot) and deliver bikes to vacant docks at stations or pick up bikes from overloaded stations; the cost of running this process through the network can be very high, which is an important issue in the management of bike sharing systems. Finding a rebalancing strategy to keep the balance of network with the least possible cost can be an ideal case for operators
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