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《Journal of Highway and Transportation Research and Development》 2017-06
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Optimizing Layout of Electric Vehicle Charging Station Based on Improved Particle Swarm Optimization Algorithm

QI Lin;YAO Jian;WANG Xin-yue;Business School,University of Shanghai for Science and Technology;  
In order to optimize the layout of electric vehicle charging station with the constraint of charging station service requirement and user charging demand,the optimization model with the goal of minimum the costs of charging station service and user needs is constructed. Combining the K central point algorithm and the cloud model hybrid adaptive particle swarm optimization algorithm, an adaptive parameter change algorithm for improving the global search ability is proposed. Using the characteristics of cloud model adaptive hybrid particle swarm algorithm,the K center point cloud model adaptive hybrid particle swarm algorithm for solving the problem of optimizing electric vehicle charging station layout is constructed. The simulation result shows that( 1) when solving the problem of optimizing electric vehicle charging station layout with the constraint of electric vehicle charging station service requirement and the user charging demand,the improved K center point cloud model adaptive hybrid particle swarm algorithm outperforms the cloud model particle swarm algorithm and the original particle swarm algorithm;( 2) compared with the basic algorithms,the improved algorithm has better efficiency and better convergence,which proved the effectiveness and feasibility of the improved algorithm.
【CateGory Index】: TP18;U491.8
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Chinese Journal Full-text Database 10 Hits
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【Co-citations】
Chinese Journal Full-text Database 10 Hits
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