A Balanced Strategy for the FFBS Operator Integrating Dispatch Area, Route, and Depot Based on Multimodel Technologies

Abstract

Bicycle scheduling is the essential strategy for balancing the demand for the public bicycle system (PBS). Existing literature pays more attention to bike scheduling models and their solutions, but seldom discusses the dispatch area and depot center. Reasonable dockless public bicycle dispatch area and optimal dockless bike dispatch depot location in the service area were discussed from the existing shared bicycle operation data in this paper. We proposed a feasible framework including bike trip network segmentation, mean-shift clustering based on the point position, VRP model, genetic algorithm, and TOPSIS evaluation method. The effectiveness and superiority of the division of the dispatch area are verified. The main evidence for this article is (1) although the cycling networks of bicycles are different at different times of the day, the results of community division are relatively stable and have great similarities. (2) The plan of the dispatch area has impacted on the operation efficiency of the PBS. For a scheduling area, the target value of the optimal scheduling strategy corresponding to different dispatch centers is obviously different. Therefore, the location of the dispatch center has a great impact on the quality of the scheduling strategy. The dispatch area determined by bike trip OD community detection has stable characteristics of scheduling costs. (3) This work is an attempt to combine big data and model technology to assist city management. We build a feasible framework to serve a balanced strategy for FFBS which can provide reasonable dispatch area, optimal dispatch depot location, dispatch truck’s route length, load action, and time window. Our proposed framework provides new ideas for regional traffic dispatching for the traffic management department and FFBS operator, which has certain practical reference significance.