Optimization models for electric vehicle service operations: A literature review

• Published in: Transportation research. Part B: methodological Vol. 128; pp. 462 - 477
• Main Authors: Shen, Zuo-Jun Max, Feng, Bo, Mao, Chao, Ran, Lun
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2019; Elsevier Science Ltd
• Subjects: Algorithms; Anxiety; Business; Dependence; Electric vehicle; Electric vehicle charging; Electric vehicles; Fossil fuels; Infrastructure; Literature review; Literature reviews; Mathematical models; Operations management; Optimization models; Optimization models and algorithms; Public policy; Service operations; State-of-the-art reviews; Optimization models and algorithms; Literature review; Electric vehicle; Service operations
• ISSN: 0191-2615; 1879-2367
• DOI: 10.1016/j.trb.2019.08.006

•We provide a review of existing operations studies of electric vehicles (EVs).•This review focuses on mathematical modeling-based solutions to EV operations management problems.•The literature is grouped into EV charging infrastructure planning, EV charging operations, and public policy and business models.•New research opportunities for operations management of EVs are suggested. Electric vehicles (EVs) are widely considered to be a solution to the problems of increasing carbon emissions and dependence on fossil fuels. However, the adoption of EVs remains sluggish due to range anxiety, long charging times, and inconvenient and insufficient charging infrastructure. Various problems with EV service operations should be addressed to overcome these challenges. This study reviews the state-of-the-art mathematical modeling-based literature on EV operations management. The literature is classified according to recurring themes, such as EV charging infrastructure planning, EV charging operations, and public policy and business models. In each theme, typical optimization models and algorithms proposed in previous studies are surveyed. The review concludes with a discussion of several possible questions for future research on EV service operations management.