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Title	Optimization Model For Electric Vehicle Charging Station Problem In Smart City
ID_Doc	40599
Authors	Abidi S.; Soltani A.
Year	2023
Published	17th International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2023 - Proceedings
DOI	http://dx.doi.org/10.1109/INISTA59065.2023.10310503
Abstract	This paper proposes an optimization model to solve electric vehicle (EV) charging station (CS) problem. It consists in assigning the best CS to an EV driver that minimizes the cost of electric power charging and destination proximity while ensuring that the overall renewable power based CS capacity is efficiently utilized. This model rests on a hybrid heuristic resolution approach (HASP). The proposed heuristic can achieve near-optimal resource utilization and significant improvement compared to state of the art algorithms and an uncontrolled CS assignment resolution approach. The experiments are carried out using published standard instances from the literature. The computational results reveal that HASP outperformed the DE-SK, BEE and TABU algorithm. The HASP is able to obtain more optimal solutions compared to the DE-SK algorithm. This is because the HASP is designed to enhance the search capability by improving the diversification using the GA's operators and the SWAP algorithm moves added to the GA can improve the intensification. © 2023 IEEE.
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