TY - GEN
T1 - A Simulation Framework for the Rebalancing and Maintenance of Bicycle-sharing Systems
AU - Jin, Yu
AU - Ruiz, Cesar
AU - Liao, Haitao
AU - Pierson, Harry
N1 - Funding Information:
HAITAO LIAO is a Professor, and John and Mary Lib White Endowed Systems Integration Chair in the Department of Industrial Engineering at University of Arkansas - Fayetteville. He received a Ph.D. in Industrial and Systems Engineering from Rutgers University in 2004. His research has been sponsored by the U.S. National Science Foundation, Department of Energy, Nuclear Regulatory Commission, Oak Ridge National Laboratory, and industry. The research findings of his group have been published in IISE Transactions, European Journal of Operational Research, Naval Research Logistics, IEEE Transactions on Reliability, IEEE Transactions on Cybernetics, The Engineering Economist, Reliability Engineering & System Safety, etc. In 2014, he served as Chair of INFORMS Quality, Statistics and Reliability (QSR) Section, and President of IISE Quality Control and Reliability Engineering (QCRE) Division. He served as Associate Editor for Journal of Quality Technology and IEEE Transactions on Reliability, and currently serves as Associate Editor for IISE Transactions on Quality and Reliability Engineering. He received the U.S. National Science Foundation CAREER Award in 2010, the IISE QCRE William A.J. Golomski Award for three times, 2013 QCRE Track Best Paper Award, Stan Ofsthun Best Paper Awards in 2015 and 2019, and the prestigious 2017 Alan O. Plait Award for Tutorial Excellence. His email address is liao@uark.edu.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Bicycle-sharing system (BSS) has attracted much attention due to its great success in providing a low-cost and environment-friendly alternative to traditional public transportation systems. In some BSSs comprised of stations with fixed docks, customer satisfaction can be measured by the availability of bikes for pick-ups and/or open docks for returns. However, it is quite common that the spatial balance of bike inventories will be broken due to customers' behavior or frequent failures of bikes and docks. As a result, constant rebalancing and maintenance services are required to sustain adequate levels of customer satisfaction. In this research, a simulation framework is developed to optimize the rebalancing and maintenance activities while satisfying customers' needs over a service area. An optimization model solved by Ant Colony Optimization is applied on the Citibike in New York City, which is considered as an example to validate the effectiveness and efficiency of the proposed simulation framework.
AB - Bicycle-sharing system (BSS) has attracted much attention due to its great success in providing a low-cost and environment-friendly alternative to traditional public transportation systems. In some BSSs comprised of stations with fixed docks, customer satisfaction can be measured by the availability of bikes for pick-ups and/or open docks for returns. However, it is quite common that the spatial balance of bike inventories will be broken due to customers' behavior or frequent failures of bikes and docks. As a result, constant rebalancing and maintenance services are required to sustain adequate levels of customer satisfaction. In this research, a simulation framework is developed to optimize the rebalancing and maintenance activities while satisfying customers' needs over a service area. An optimization model solved by Ant Colony Optimization is applied on the Citibike in New York City, which is considered as an example to validate the effectiveness and efficiency of the proposed simulation framework.
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U2 - 10.1109/WSC40007.2019.9004805
DO - 10.1109/WSC40007.2019.9004805
M3 - Conference contribution
AN - SCOPUS:85081131900
T3 - Proceedings - Winter Simulation Conference
SP - 819
EP - 829
BT - 2019 Winter Simulation Conference, WSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Winter Simulation Conference, WSC 2019
Y2 - 8 December 2019 through 11 December 2019
ER -