Optimizing the Location of Opportunity Chargers for Urban Buses Using a Multi-Criteria Decision-Making Approach

As cities push toward cleaner transportation modes, the development of efficient and effective charging facilities is crucial for the successful operation of electric bus services. Introducing various charging methods, in addition to traditional depot charging, is essential to enhance the operational efficiency of electric buses. This paper presents a methodology for implementing opportunity charging along bus routes, utilizing a Non-dominated Sorting Genetic Algorithm (NSGA-II) combined with decision-making techniques. The algorithm identifies a set of optimal solutions, which are then further analyzed using decision-making techniques. This approach offers a valuable framework, ensuring that the solutions are adaptable to real-world conditions and cater to the different needs of stakeholders. Consequently, the solutions are not only optimal in theoretical models but also practical, implementable in complex urban environments, and scalable for broader application.