摘要
AbstractElectric Vehicles (EVs) have a critical role in the future of sustainable transportation systems. Recently, improving the infrastructure for EVs has been a major focus of organizations around the world, such as local and federal governments, energy companies, and automotive original equipment manufacturers. In this article, we present a service network design framework to improve the infrastructure for EVs with quality of service constraints taken into consideration. We present a novel charging station location model with capacity allocation. The model maximizes the EV traffic flow captured and minimizes the average service time for drivers. The model formulation allows for assessing capacity and quality of service trade-offs, and operational insights are presented to reflect drivers’ expectations. We demonstrate an application for the solution approach on a real road network and evaluate the performance based on both computational efficiency and solution quality. Our results highlight how charging times at stations affect the quality of service in the whole service system by quantifying the improvements in flow coverage while reducing waiting times. The value of faster chargers in increasing coverage and reducing the average waiting times is also highlighted in relation to a service provider’s budget constraints.Keywords: Locationelectric vehicleschargersnetwork designflow capture Additional informationNotes on contributorsİbrahim Çaparİbrahim Çapar is an assistant professor at the Applied Statistics and Operations Research Department at Bowling Green State University. He earned his PhD in the Operations Management program at the University of Alabama. His research interests mainly focus on applied, large-scale optimization problems with applications in routing. He has been an active member of several professional organizations, including INFORMS and POMS.Özgür M. ArazÖzgür M. Araz is the Ron and Carol Cope Professor of Supply Chain Management and Analytics in the College of Business at the University of Nebraska-Lincoln, NE, USA. His main research areas are simulation modeling, business analytics, healthcare operations, and supply network design. His research appeared in journals, such as Decision Sciences, Production and Operations Management, INFORMS Journal on Computing, Decision Support Systems, International Journal of Production Economics, Annals of Operations Research, IEEE Transactions on Engineering Management and many other prestigious journals. Dr. Araz is on the editorial board of Production and Operations Management journal and serves as an associate editor for Decision Sciences, Transportation Research Part-E, and IISE Transactions of Healthcare Systems Engineering. He is also the area editor for Public Health Informatics in Health Systems journal.İsmail Çaparİsmail Çapar is an associate professor at the Industrial Distribution Program at Texas A&M University. His research interests include inventory and transportation coordination, distribution and logistics management, warehouse design and optimization, supply chain network optimization, transportation issues during incidents of national significance, location/pricing decisions for alternative fuel vehicles.