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Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations

Author

Listed:
  • Guiwu Wei
  • Fan Lei
  • Rui Lin
  • Rui Wang
  • Yu Wei
  • Jiang Wu
  • Cun Wei

Abstract

Electric vehicles (EVs) could be regarded as one of the most innovative and high technologies all over the world to cope with the fossil fuel energy resource crisis and environmental pollution issues. As the initiatory task of EV charging station (EVCS) construction, site selection play an important part throughout the whole life cycle, which is deemed to be multiple attribute group decision making (MAGDM) problem involving many experts and many conflicting attributes. In this paper, a grey relational analysis (GRA) method is investigated to tackle the probabilistic uncertain linguistic MAGDM in which the attribute weights are completely unknown information. Firstly, the definition of the expected value is then employed to objectively derive the attribute weights based on the CRiteria Importance Through Intercriteria Correlation (CRITIC) method. Then, the optimal alternative is chosen by calculating largest relative relational degree from the probabilistic uncertain linguistic positive ideal solution (PULPIS) which considers both the largest grey relational coefficient from the PULPIS and the smallest grey relational coefficient from the probabilistic uncertain linguistic negative ideal solution (PULNIS). Finally, a numerical case for site selection of electric vehicle charging stations (EVCS) is designed to illustrate the proposed method. The result shows the approach is simple, effective and easy to calculate.

Suggested Citation

  • Guiwu Wei & Fan Lei & Rui Lin & Rui Wang & Yu Wei & Jiang Wu & Cun Wei, 2020. "Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 33(1), pages 828-846, January.
  • Handle: RePEc:taf:reroxx:v:33:y:2020:i:1:p:828-846
    DOI: 10.1080/1331677X.2020.1734851
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    Cited by:

    1. Sema Kayapinar Kaya & Ejder Ayçin & Dragan Pamucar, 2023. "Evaluation of social factors within the circular economy concept for European countries," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(1), pages 73-108, March.
    2. Hamidreza Qane'ei Kenarsari & Narges Banaeian & Mahdi Khani, 2024. "Selecting a sustainable array of machinery by integrating analytic hierarchy process with gray relational analysis," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(2), pages 109-119.

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