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Cui, S. H. (2019). Research on Path Planning and Design of Mobile Charging Service. Master’s Thesis, Beijing Jiaotong University.
https://kns.cnki.net/kcms2/article/abstract?v=lvdN5-6qPlPch7LT5hffFcm3YCY_zHnanNj_AaQsj8SQKEsORjqwWU8DjYRVPbW7f9cyCYm5JLI5gR6X0BGngzIchfixgo3nqfKbMuG3tUNzRgxop2oPTaMSPIX3H4EW3e1c8BPoBOKmXQi0RgaU--Da3_qTtmGD4_zmZAAQB2fgWrO0cPlFPninRwhYmW62gMCjtYPtGFU=&uniplatform=NZKPT&language=CHS

has been cited by the following article:

• TITLE: Research on the Operation Mode and Path Optimization of Mobile Charging Service for New Energy Vehicles

  AUTHORS: Yang Han, Hanlin Gu, Yufei Shen, Rui Ying, Ying Li

  KEYWORDS: New Energy Vehicles, Mobile Charging Services, Path Planning, Heuristic Algorithms, Case Solving

  JOURNAL NAME: American Journal of Industrial and Business Management, Vol.14 No.12, December 27, 2024

  ABSTRACT: This paper first comprehensively combs and analyzes the different operation modes of China’s new energy vehicle mobile charging service industry through literature reading, enterprise research, theoretical application and other methods, summarizes the characteristics of various enterprise operation models, and outlines the current market pattern of the mobile charging service industry. On this basis, in view of the scenario of multiple mobile charging robots charging multiple new energy vehicles that need to be charged, heuristic algorithms such as simulated annealing algorithm and ant colony algorithm were used in PyCharm to carry out the path planning modeling and case solving analysis of the “multi-traveling salesman problem”. Finally, this paper summarizes the results of the study, hoping to promote the high-quality development of the mobile charging service industry for new energy vehicles.