期刊
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
卷 40, 期 -, 页码 123-142出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2014.01.008
关键词
Electric vehicle; Shared-taxi; EV charging; Bi-level optimization; Facility location; Stochastic demand; Simulation; Refueling
资金
- Korea Transport Institute (KOTI), as part of Electric Vehicle Research on Business
- National Research Council for Economics, Humanities and Social Science, South Korea
- Canada Research Chairs program
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 km(2), a budget of 100 charging stations, and up to 22 candidate charging locations, against a benchmark naive 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. (C) 2014 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据