An integrated framework for electric vehicle rebalancing and staff relocation in one-way carsharing systems: Model formulation and Lagrangian relaxation-based solution approach
An integrated framework for electric vehicle rebalancing and staff relocation in one-way carsharing systems: Model formulation and Lagrangian relaxation-based solution approach
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DOI：
10.1016/j.trb.2018.09.014
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发表时间：
2018-11
期刊：
影响因子：
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通讯作者：
Meng Zhao;X. Li;Jiateng Yin;J. Cui;Lixing Yang;S. An
中科院分区：
文献类型：
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作者：
Meng Zhao;X. Li;Jiateng Yin;J. Cui;Lixing Yang;S. An
在单向电动汽车(EV)拼车系统中，一个需要解决的实际问题是电动汽车在不同拼车站点的用户预订与空间和时间相关的不平衡。在实践中，适当的电动汽车再平衡操作可以用有限的资源满足用户预订，并有效地节省系统投资。本文提出了一个综合框架，该框架可以在战略层面上确定电动汽车和员工的最优配置方案，同时考虑运营中的电动汽车搬迁和员工搬迁决策，以最小化总成本，包括电动汽车和员工投资、电动汽车再平衡和员工搬迁成本。在该框架中，电动汽车和员工的调度路径在规划时间范围内用两组时空路径表示，然后将所考虑的问题表示为混合整数线性规划模型(MILP)。该模型明确地考虑了(1)通过动态地重新平衡电动汽车和重新安置员工以保持拼车系统的服务质量来满足依赖于时间的用户预订；(2)有限行驶距离的电动汽车电池容量和电动汽车在停车场的充电过程。提出了一种基于拉格朗日松弛的求解方法，将原问题分解为几组计算效率较高的子问题。为了产生高质量的解，我们还根据拉格朗日乘子值提出了一种基于动态规划的三阶段实现算法。通过一个算例和一个实际案例(基于华盛顿州西雅图的运营数据)，验证了所建立模型的适用性和所提出方法的有效性。
In one-way electric vehicle (EV) carsharing systems, a practical issue that needs to be addressed is the imbalance of EVs with respect to the spatial time-dependent user reservations at different carsharing stations. In practice, appropriate EV rebalancing operations can satisfy user reservations with limited resources and effectively save system investments. This paper proposes an integrated framework that can determine the optimal allocation plan of EVs and staff on the strategic level while considering the operational EV relocation and staff relocation decisions, in order to minimize the total cost, including the EV and staff investment, EV rebalancing and staff relocation costs. In this framework, the dispatching routes of EVs and staff are represented by two sets of space-time paths in the planning time horizon by using a space-time network representation, and the considered problem is then formulated into a mixed-integer linear programming model (MILP). This model explicitly considers (1) the satisfaction of time-dependent user reservations through dynamically rebalancing EVs and relocating staff to keep the service quality of carsharing system, and (2) the EV battery capacity with limited traveling distance and the charging process of EVs at parking stations. A Lagrangian relaxation-based solution approach is developed to decompose the primal problem into several sets of computationally efficient subproblems. In order to generate good-quality solutions, we also propose a three-phase implementing algorithm based on dynamic programming according to the values of Lagrangian multipliers. An illustrative numerical example and a real-world case study (based on the operation data of Seattle, WA) are conducted to verify the applicability of the formulated model and effectiveness of the proposed approach.