Optimization Model for the Supply Volume of Bike-Sharing: Case Study in Nanjing, China

In order to solve the oversupply and repositioning problems of bike-sharing, this paper proposes an optimization model to obtain a reasonable supply volume scheme for bike-sharing and infrastructure configuration planning. The optimization model is constrained by the demand for bike-sharing, urban t...

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Bibliographic Details
Published in:Information (Basel) 2021-05, Vol.12 (5), p.182
Main Authors: Yu, Jiajie, Ji, Yanjie, Yi, Chenyu, Kuai, Chenchen, Samal, Dmitry Ivanovich
Format: Article
Language:English
Subjects:
Bicycles
Bicycling
bike-sharing
Carrying capacity
Central business districts
Cities
CPLEX
Integer programming
Maintenance costs
Mixed integer
mixed integer programming
Network management systems
Optimization
Optimization models
Parking facilities
Regularization methods
Roads
supply volume
Traffic capacity
Traffic models
Workloads
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Summary:In order to solve the oversupply and repositioning problems of bike-sharing, this paper proposes an optimization model to obtain a reasonable supply volume scheme for bike-sharing and infrastructure configuration planning. The optimization model is constrained by the demand for bike-sharing, urban traffic carrying capacity (road network and parking facilities carrying capacities), and the flow conservation of shared bikes in each traffic analysis zone. The model was formulated through mixed-integer programming with the aim of minimizing the total costs for users and bike-sharing enterprises (including the travel cost of users, production and maintenance costs of shared bikes, and repositioning costs). CPLEX was used to obtain the optimal solution for the model. Then, the optimization model was applied to 183 traffic analysis zones in Nanjing, China. The results showed that not only were user demands met, but the load ratios of the road network and parking facilities with respect to bike-sharing in each traffic zone were all decreased to lower than 1.0 after the optimization, which established the rationality and effectiveness of the optimization results.
ISSN:2078-2489
2078-2489
DOI:10.3390/info12050182