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A Data-Driven Optimization Method for Reallocating the Free-Floating Bikes

  • Ming LiuEmail author
  • Xifen Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11434)

Abstract

Free-floating bike sharing (FFBS) is a new bike sharing mode when compared to the traditional station-based bike sharing (SBBS). It brings convenience for users since bikes can be picked up and returned anywhere but not the fixed stations. However, it also brings difficulty for managers because reallocation of free-floating bikes is totally different from any traditional ones. Using data-driven method, we define two types of nodes in this paper (i.e., easily and hardly accessed nodes), to represent different convenience levels of getting bikes from the FFBS. We collect bikes at hardly accessed nodes and reallocate them to the easily accessed nodes. Our objective is to move the needed bikes in the shortest distance and meanwhile to maximize the operation revenue. The problem is formulated as a multi-objective mixed integer programming model and an effective algorithm is designed to solve it. The test results can provide several constructive suggestions for reallocating the free-floating bikes.

Keywords

Free-floating bike sharing Static reallocation Multi-objective optimization 

Notes

Acknowledgments

This work was supported by National Natural Science Foundation of China (No. 71771120) and MOE (Ministry of Education) Project of Humanities and Social Sciences (No. 17YJA630058).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Economics and ManagementNanjingPeople’s Republic of China

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