元启发式
计算机科学
充电站
电动汽车
全球定位系统
集合(抽象数据类型)
电池(电)
整数规划
数学优化
运筹学
群体行为
粒子群优化
算法
人工智能
电信
功率(物理)
数学
程序设计语言
物理
量子力学
作者
Chaima Taieb,Takwa Tlili,Issam Nouaouri,Saoussen Krichen,Hamid Allaoui
标识
DOI:10.1080/01969722.2023.2247260
摘要
AbstractIn this article, we present a comprehensive study regarding the problem of allocating a fleet of electric vehicles to charging stations according to charging time and battery constraints. Each charging station’s capacity as well as the necessary charging time is known in advance while each vehicle’s arrival time is provided by a GPS device. We provide an integer programming model solved with an exact method to effectively handle this combinatorial problem along with a set of metaheuristic algorithms. To evaluate the performance of this solution framework, computational experiments are conducted on large-scale randomly generated instances simulating a real-world scenario.Keywords: Artificial bee colonycombinatorial optimizationelectric vehiclesgenetic algorithmmetaheuristicsparticle swarm optimizationsmart city Disclosure statementNo potential conflict of interest was reported by the authors.Correction StatementThis article has been corrected with minor changes. These changes do not impact the academic content of the article.Notes1 Global EV Outlook 2019 – Analysis - IEA
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