Journal of Jilin University (Information Science Edition) ›› 2020, Vol. 38 ›› Issue (3): 371-378.

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Public Bicycle Operation Analysis and Scheduling Model Based on Big Data

LI Mingming   

  1. Management Center of Big Data and Network,Jilin University,Changchun 130025,China
  • Received:2019-08-19 Online:2020-05-24 Published:2020-06-24

Abstract: In order to solve the problem of difficult to borrow bicycles during the rush hour of the public bicycle
system,and improve the operating efficiency and user satisfaction of the public bicycle system,the operation of
the existing public bicycle system in a certain city was used as the research object. The borrowing and return
rules of the system analyze the operating characteristics of public bicycles,study the time characteristics and
turnover characteristics of public bicycles,and provide a data basis for the establishment of scheduling models.
Finally,a better public bicycle scheduling model is established through the ant colony algorithm. The ant colony
algorithm,establishs a static dispatching route optimization model,and obtains the optimal dispatching route for
dispatching vehicles. Thus,the problem of difficult to borrow bicycles during peak hours is effectively solved,
reducing the time required for dispatching and improving work efficiency.

Key words: public bicycles, scheduling model, distribution characteristics, turnaround characteristics, ant
colony algorithm

CLC Number: 

  • TP312