@article{Qi2018, 
author = {Lin Qi and Jian Yao and Xinyue Wang},
title = {Improved Particle Swarm Optimization Algorithm to Solve the Problem of Layout Optimization of Electric Vehicle Charging Stations},
year = {2018},
journal = {Journal of Highway and Transportation Research and Development (English Edition)},
volume = {12},
number = {2},
pages = {96-103},
keywords = {Traffic engineering, layout optimization of electric vehicle charging station, improved particle swarm optimization algorithm, particle swarm optimization algorithm, cloud model, Voronoi diagram},
url = {https://www.sciopen.com/article/10.1061/JHTRCQ.0000631},
doi = {10.1061/JHTRCQ.0000631},
abstract = {In charging station services, user charging requirements limit the layout optimization of charging stations to realize total cost minimization. By combining the k-center algorithm and cloud model particle swarm algorithm, this study puts forward a method to improve the global search ability of the adaptive parameter adjustment strategy. A simulation is performed accordingly. Results show that when solving the layout optimization problem for charging stations, the improved adaptive hybrid algorithm that combines the k-center and cloud model particle swarm algorithm outperforms the original cloud model particle swarm algorithm and the basic particle swarm optimization algorithm. The improved algorithm is thus effective.}
}