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Relocation optimization of electric cars in one-way car-sharing systems: modeling, exact solving and heuristics algorithms

机译:单向共享汽车中电动汽车的位置优化:建模,精确求解和启发式算法

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摘要

Car-sharing system with electric cars is a very convenient service for urban transportation: it allows users to pick up a vehicle at a station and rent it during a short time. To manage this kind of system in the best way, it is necessary to solve the critical problem of vehicle stock imbalance across the stations. Several decision levels must be considered to balance the car distribution by taking into account the quality of service and the system operation cost. To this end, a linear programming model is proposed to formalize the problem in a mathematical framework, which allows the computation of optimal vehicle distribution strategies. To make our solution time efficient and usable for solving large problems, a greedy algorithm and a tabu search algorithm are proposed. These two algorithms are applied to the Auto Bleue network in Nice and its surrounding (France) using extensive simulations. Besides, an integrated mapping method is provided within the Geographical Information System QGIS to estimate flows and their locations. Numerical results demonstrate that the tabu search algorithm is able to find near-optimal solutions and good compromises between client satisfaction, number of staff agents and vehicles used, and computing time.
机译:带电动汽车的汽车共享系统对于城市交通而言是一项非常便捷的服务:它允许用户在短时间内在车站取车并租车。为了以最佳方式管理这种系统,有必要解决跨站车辆存量不平衡这一关键问题。通过考虑服务质量和系统运营成本,必须考虑几个决策级别来平衡汽车分配。为此,提出了线性规划模型以在数学框架中将问题形式化,从而可以计算最佳车辆分配策略。为了使我们的解决方案时间高效且可用于解决大问题,提出了一种贪婪算法和禁忌搜索算法。通过广泛的仿真,这两种算法已应用于尼斯及其周围地区(法国)的Auto Bleue网络。此外,在地理信息系统QGIS中提供了一种集成的映射方法来估计流量及其位置。数值结果表明,禁忌搜索算法能够找到接近最佳的解决方案,并且可以在客户满意度,使用的工作人员和车辆数量以及计算时间之间取得良好的折衷。

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