Linear control policies for online vehicle relocation in shared mobility systems
Linear control policies for online vehicle relocation in shared mobility systems
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DOI：
10.1016/j.eswa.2022.118417
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发表时间：
2022-08
期刊：
影响因子：
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通讯作者：
Y. Yoshida;Yuichi Takano
中科院分区：
文献类型：
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作者：
Y. Yoshida;Yuichi Takano
在基于单向站的共享移动系统中，其中系统用户共享车辆以在车辆站之间进行行程，单向行程的累积不可避免地导致站之间的车辆不平衡。为了纠正这些不平衡，我们专注于有效地使用线性控制策略，从用户行程的历史计算在线车辆重新定位。我们的神经网络为基础的优化模型计算线性控制策略制定为一个线性优化问题。使用真实世界的数据集的计算结果表明，我们的方法提供了很高的重新定位性能与短的在线计算时间。
In one-way station-based shared mobility systems, where system users share vehicles for making trips between vehicle stations, the accumulation of one-way trips inevitably causes vehicle imbalances between stations. To correct these imbalances, we focus on the effective use of linear control policies for calculating online vehicle relocations from a history of user trips. Our scenario-based optimization model for computing linear control policies is formulated as a linear optimization problem. Computational results using a real-world dataset demonstrate that our method provides high relocation performance with short online computation times.