Stochastic Dynamic Itinerary Interception Refueling Location Problem with Queue Delay for Electric Taxi Charging Stations
Stochastic Dynamic Itinerary Interception Refueling Location Problem with Queue Delay for Electric Taxi Charging Stations
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DOI：
10.1016/j.trc.2014.01.008
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发表时间：
2014-03
期刊：
影响因子：
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通讯作者：
Jaeyoung Jung;Joseph Y. J. Chow;R. Jayakrishnan;Ji Young Park
中科院分区：
文献类型：
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作者：
Jaeyoung Jung;Joseph Y. J. Chow;R. Jayakrishnan;Ji Young Park
提出了一种新的设施选址模型及其求解算法，其特点是：（1）以行程拦截代替流量拦截;（2）以随机需求作为动态服务请求;（3）避免延误。这些功能对于分析以连接的集中调度方式运行的电池供电的电动共享出租车至关重要。该模型和解决方案的方法是基于一个双层，仿真优化框架，结合上层多服务器分配模型与延迟和较低层次的调度仿真的基础上，由荣格和Jayakrishnan早期的工作。该解决方案的算法进行了测试，在韩国首尔，跨越603平方公里，预算的100个充电站，和多达22个候选充电位置，对基准“天真”的遗传算法，不考虑循环之间的相互作用的出租车充电需求和充电器分配与队列延迟。结果表明，该模型不仅能够解决具有随机动态拦截和排队延迟的充电站选址问题，而且双层求解方法在实现排队延迟、出租车服务总运营时间和服务请求拒绝率等方面均优于基准算法.此外，我们展示了在上限情况下，当充电站的数量是无限的，有多少额外的好处是可能的服务水平。
A new facility location model and a solution algorithm are proposed that feature (1) itinerary-interception instead of flow-interception; (2) stochastic demand as dynamic service requests; and (3) queueing delay. These features are essential to analyze battery-powered electric shared-ride taxis operating in a connected, centralized dispatch manner. The model and solution method are based on a bi-level, simulation–optimization framework that combines an upper level multiple-server allocation model with queueing delay and a lower level dispatch simulation based on earlier work by Jung and Jayakrishnan. The solution algorithm is tested on a fleet of 600 shared-taxis in Seoul, Korea, spanning 603 km2, a budget of 100 charging stations, and up to 22 candidate charging locations, against a benchmark “naïve” genetic algorithm that does not consider cyclic interactions between the taxi charging demand and the charger allocations with queue delay. Results show not only that the proposed model is capable of locating charging stations with stochastic dynamic itinerary-interception and queue delay, but that the bi-level solution method improves upon the benchmark algorithm in terms of realized queue delay, total time of operation of taxi service, and service request rejections. Furthermore, we show how much additional benefit in level of service is possible in the upper-bound scenario when the number of charging stations is unbounded.