Battery-electric transit vehicle scheduling with optimal number of stationary chargers
Battery-electric transit vehicle scheduling with optimal number of stationary chargers
复制标题
具有最佳固定充电器数量的电动交通车辆调度
DOI：
10.1016/j.trc.2020.02.009
复制
发表时间：
2020-05-01
影响因子：
8.3
通讯作者：
Ceder, Avishai (Avi)
中科院分区：
文献类型：
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作者：
Liu, Tao;Ceder, Avishai (Avi)
由于零排放等社会和经济效益，电动汽车(EVS)目前正被越来越多的全球公交机构所采用。考虑到有限的行驶里程和充电要求的限制，最具挑战性的任务之一是有效地调度一组电动汽车。研究公交终点站安装固定电池充电器的电池-电动公交车辆调度问题。文中给出了该问题数学公式的两个等价版本。第一个公式基于赤字函数理论，第二个公式是一个等价的双目标整数规划模型。数学规划优化的第一个目标是最小化所需的电动汽车总数，而第二个目标是最小化所需的电池充电器总数。针对这一双目标BET-VSP问题，提出了两种求解方法。首先，提出了一种基于词典方法的两阶段构造优化求解过程。其次，提出了一种调整的最大流法。文中以三个数值算例作为说明手段，结合新加坡的实际案例分析，说明了解决问题的方法。结果表明，所提出的数学规划模型和求解方法是有效的，有可能应用于大规模实际BET-VSP问题的求解。
Because of zero emissions and other social and economic benefits, electric vehicles (EVs) are currently being introduced in more and more transit agencies around the world. One of the most challenging tasks involves efficiently scheduling a set of EVs considering the limited driving range and charging requirement constraints. This study examines the battery-electric transit vehicle scheduling problem (BET-VSP) with stationary battery chargers installed at transit terminal stations. Two equivalent versions of mathematical formulations of the problem are provided. The first formulation is based on the deficit function theory, and the second formulation is an equivalent bi-objective integer programming model. The first objective of the math-programming optimization is to minimize the total number of EVs required, while the second objective is to minimize the total number of battery chargers required. To solve this bi-objective BET-VSP, two solution methods are developed. First, a lexicographic method-based two-stage construction-and-optimization solution procedure is proposed. Second, an adjusted max-flow solution method is developed. Three numerical examples are used as an expository device to illustrate the solution methods, together with a real-life case study in Singapore. The results demonstrate that the proposed math-programming models and solution methods are effective and have the potential to be applied in solving large-scale real-world BET-VSPs.