Shared Bikes Scheduling Under Users’ Travel Uncertainty

With the rise of green concept, shared bikes are booming. The accompanying unbalanced scheduling problem is a scientific problem that needs to be solved urgently. Aiming at the problem of shared bikes scheduling with travel uncertainty, a multi-objective integer programming model is established base...

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Main Authors: Zhi-Yong Zhang, Xiao Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8939451/
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spelling doaj-7f8f61a3e09944d98f3cd48b1f43c5ff2021-03-30T02:23:05ZengIEEEIEEE Access2169-35362020-01-0183123314310.1109/ACCESS.2019.29616288939451Shared Bikes Scheduling Under Users’ Travel UncertaintyZhi-Yong Zhang0https://orcid.org/0000-0003-1729-9507Xiao Zhang1https://orcid.org/0000-0001-7174-5657School of Economics and Management, Xidian University, Xi’an, ChinaSchool of Economics and Management, Xidian University, Xi’an, ChinaWith the rise of green concept, shared bikes are booming. The accompanying unbalanced scheduling problem is a scientific problem that needs to be solved urgently. Aiming at the problem of shared bikes scheduling with travel uncertainty, a multi-objective integer programming model is established based on the consideration of static demand of fix time period, station capacity limit, penalty cost and other practical factors. In addition, this paper gives the basic formula to calculate the parameters in the model. An algorithm based on “ant colony algorithm” is then given to solve the model. Taking the massive data provided by the “Mobike” company in 2017 as an example, this paper uses the program analysis data to prove the feasibility and effectiveness of the model and get the initial optimization plan. Finally, the data simulation is carried out to verify the feasibility and accuracy of the optimization scheme and the optimization scheme is adjusted accordingly to obtain the final optimization scheme. The research results show that the final optimization scheme proposed in this paper has certain reference value for the scheduling problem of Shanghai “Mobike”.https://ieeexplore.ieee.org/document/8939451/Shared bikestravel uncertaintyschedulingstatic demand intervalrebalancing
collection DOAJ
language English
format Article
sources DOAJ
author Zhi-Yong Zhang
Xiao Zhang
spellingShingle Zhi-Yong Zhang
Xiao Zhang
Shared Bikes Scheduling Under Users’ Travel Uncertainty
IEEE Access
Shared bikes
travel uncertainty
scheduling
static demand interval
rebalancing
author_facet Zhi-Yong Zhang
Xiao Zhang
author_sort Zhi-Yong Zhang
title Shared Bikes Scheduling Under Users’ Travel Uncertainty
title_short Shared Bikes Scheduling Under Users’ Travel Uncertainty
title_full Shared Bikes Scheduling Under Users’ Travel Uncertainty
title_fullStr Shared Bikes Scheduling Under Users’ Travel Uncertainty
title_full_unstemmed Shared Bikes Scheduling Under Users’ Travel Uncertainty
title_sort shared bikes scheduling under users’ travel uncertainty
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description With the rise of green concept, shared bikes are booming. The accompanying unbalanced scheduling problem is a scientific problem that needs to be solved urgently. Aiming at the problem of shared bikes scheduling with travel uncertainty, a multi-objective integer programming model is established based on the consideration of static demand of fix time period, station capacity limit, penalty cost and other practical factors. In addition, this paper gives the basic formula to calculate the parameters in the model. An algorithm based on “ant colony algorithm” is then given to solve the model. Taking the massive data provided by the “Mobike” company in 2017 as an example, this paper uses the program analysis data to prove the feasibility and effectiveness of the model and get the initial optimization plan. Finally, the data simulation is carried out to verify the feasibility and accuracy of the optimization scheme and the optimization scheme is adjusted accordingly to obtain the final optimization scheme. The research results show that the final optimization scheme proposed in this paper has certain reference value for the scheduling problem of Shanghai “Mobike”.
topic Shared bikes
travel uncertainty
scheduling
static demand interval
rebalancing
url https://ieeexplore.ieee.org/document/8939451/
work_keys_str_mv AT zhiyongzhang sharedbikesschedulingunderusersx2019traveluncertainty
AT xiaozhang sharedbikesschedulingunderusersx2019traveluncertainty
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