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contributor authorQi Lin;Yao Jian;Wang Xin-yue
date accessioned2019-02-26T07:37:03Z
date available2019-02-26T07:37:03Z
date issued2018
identifier otherJHTRCQ.0000631.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4248296
description abstractIn 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.
publisherAmerican Society of Civil Engineers
titleImproved Particle Swarm Optimization Algorithm to Solve the Problem of Layout Optimization of Electric Vehicle Charging Stations
typeJournal Paper
journal volume12
journal issue2
journal titleJournal of Highway and Transportation Research and Development (English Edition)
identifier doi10.1061/JHTRCQ.0000631
page96
treeJournal of Highway and Transportation Research and Development (English Edition):;2018:;Volume ( 012 ):;issue: 002
contenttypeFulltext


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