Electric Vehicle Charging Station Layout for Tourist Attractions Based on Improved Two-Population Genetic PSO
Shuang Che,
Yan Chen and
Longda Wang (ldwangdl@sina.com)
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Shuang Che: School of Shipping Economics and Management, Dalian Maritime University, Dalian 116026, China
Yan Chen: School of Shipping Economics and Management, Dalian Maritime University, Dalian 116026, China
Longda Wang: School of Automation and Electrical Engineering, Dalian Jiaotong University, Dalian 116028, China
Energies, 2023, vol. 16, issue 2, 1-17
Abstract:
In this paper, the optimization issue of electric vehicle charging station layout (EVCSL) for tourist attractions is addressed, and an improved PSO is used to solve the optimization issue. Specifically, the improved particle swarm optimization (PSO) is proposed to obtain an appreciative planning solution of EVCSL, and dynamic weight adjustment strategy and integration into the two-population genetic mode are proposed to improve the optimization quality for PSO. Simulation results show that the proposed improvement strategies can increase the optimization quality for PSO effectively so that a more appreciative planning solution of EVCSL can be obtained.
Keywords: electric vehicle charging station layout (EVCSL); tourist attractions; improved particle swarm optimization (PSO); two-population genetic mode (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:2:p:983-:d:1036928
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