This approach demonstrates cost-efficiency and coverage in electric vehicle charging stations, highlighting sustainable infrastructure deployment.
The rapid growth of electric vehicles (EVs) is steered by the progress in technology, government policies and preservation of mother nature. This surge is transforming the automotive industry, necessitating the expansion of charging infrastructure to meet rising demand, ensure accessibility and minimize operational costs. This paper presents an optimal deployment strategy for electric vehicle charging stations (EVCS) using the Salp Swarm Optimization Algorithm (SSA). The idea is based on the way salps swarm in the ocean. The proposed SSA-based approach is tested in multiple scenarios to demonstrate that SSA effectively balances exploration and exploitation, yielding superior solutions in terms of coverage, cost-efficiency and scalability. The algorithm also adapts well to dynamic demand patterns and different constraints, making it a robust solution for real-world EV infrastructure deployment. This research highlights the potential of SSA in optimizing EVCS deployment problem, aiding in the advancement of sustainable and effective urban transportation systems.
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Sharma et al. (2025) studied this question.
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