Charging station location problem: A comprehensive review on models and solution approaches

Charging infrastructure planning has a strategic impact on promoting the use of electric vehicles (EVs) and other alternative fuel vehicles. Importantly, decision makers need to answer the question on the number and location of charging stations in a way to satisfy customer recharging demand and meet certain restrictions imposed by real-life considerations. In this context, we consider the charging station location problem (CSLP), which belongs to the category of facility location problems and seeks to optimize the locations of charging stations. A growing body of literature has developed on this subject in recent years. Various approaches have been proposed to model the problem taking into account different features, constraints, decisions and performance measures as well as the dynamic and stochastic components inherent to the problem. Moreover, efficiently solving CSLP, particularly when applied to real-life case-studies, might be challenging in practice. Considerable effort has thus been made by researchers to develop innovative solution methods based on exact or heuristic approaches to obtain good quality solutions within short computation times. Therefore, we provide in this paper a comprehensive review on the literature relevant to CSLP, with a particular focus on modeling and solving the problem. We analyze the literature from different perspectives including demand representation, demand coverage approaches, objective functions, side constraints, decision variables, model structure as well as time dependency and uncertainty on the problem parameters. We also present various ways of classifying existing works, which allows readers to capture different aspects of the problem that researchers have tended to focus on and identify opportunities for further developments. We believe our work could be helpful to researchers by providing an overview of the CSLP literature and suggesting perspectives for future research in the field.