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Paper details
Number 4 - December 2022
Volume 32 - 2022
A coordinated optimization of rewarded users and employees in relocating station-based shared electric vehicles
Lan Yu, Jiaming Liu, Zhuo Sun
Abstract
To solve the mismatch between the supply and demand of shared electric vehicles (SEVs) caused by the uneven distribution
of SEVs in space and time, an SEV relocating optimization model is designed based on a reward mechanism. The aim of
the model is to achieve a cost-minimized rebalancing of the SEV system. Users are guided to attend the relocating SEVs
by a reward mechanism, and employees can continuously relocate multiple SEVs before returning to the supply site. The
optimization problem is solved by a heuristic column generation algorithm, in which the driving routes of employees are
added into a pool by column generation iteratively. In the pricing subproblem of column generation, the Shuffled Complex
Evolution–University of Arizona (SCE–UA) is designed to generate a driving route. The proposed model is verified with
the actual data of the Dalian city. The results show that our model can reduce the total cost of relocating and improve the service efficiency.
Keywords
shared electric vehicles, user reward mechanism, collaborative relocating, SCE–UA