Research on Electric Vehicle Charging Station Location Based on Multiple Objective Snake Optimizer

Liying Li and Haipan Song
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Liying Li: Liaoning Technical University, School of Business and Management
Haipan Song: Liaoning Technical University, School of Business and Management

A chapter in Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), 2024, pp 1419-1427 from Springer

Abstract: Abstract In view of the characteristics that the performance of electric vehicle power battery is easily affected by low temperature environment, by taking the influence of low temperature environment on the energy consumption of electric vehicle into account, a bi-objective location model was constructed to minimize the user's generalized travel cost and the total construction cost, and Multiple Objective Snake Optimizer (MOSO) was designed to solve the model. The feasibility of the model and the effectiveness of the algorithm are verified by taking the Central China and the Northeast China as examples, and the influence of the difference of siting strategy and the change of charging demand on siting strategy is explored.

Keywords: charging facility; bi-objective site selection; Multiple Objective Snake Optimizer (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-256-9_143

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DOI: 10.2991/978-94-6463-256-9_143

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