Pythagorean fuzzy MCDM method based on CoCoSo and CRITIC with score function for 5G industry evaluation

  • Xindong Peng
  • Xiang Zhang
  • Zhigang LuoEmail author


The 5G industry is of great concern to countries to formulate a major national strategy for 5G planning, promote industrial upgrading, and accelerate their economic and technological modernization. When considering the 5G industry evaluation, the basic issues involve strong uncertainty. Pythagorean fuzzy sets, depicted by membership degree and non-membership degree, are a more resultful means for capturing uncertainty. In this paper, the comparison issue in Pythagorean fuzzy environment is disposed by proposing novel score function. Next, the \(\ominus \) and \(\oslash \) operations are defined and their properties are proved. Later, the objective weight is calculated by Criteria Importance Through Inter-criteria Correlation method. Meanwhile, the combined weight is determined by reflecting both subjective weight and the objective weight. Then, the Pythagorean fuzzy decision making algorithm based Combined Compromise Solution is developed. Lastly, the validity of algorithm is expounded by the 5G evaluation issue, along with their sensitivity analysis. The main advantages of proposed algorithm are: (1) have no counterintuitive phenomena; (2) without division or antilogarithm by zero problem; (3) own stronger ability to distinguish alternatives.


5G industry evaluation Pythagorean fuzzy sets Score function CoCoSo CRITIC 



The authors are very appreciative to the reviewers for their precious comments which enormously ameliorated the quality of this paper. Our work is sponsored by the National Natural Science Foundation of China (Nos. 61462019, 61806213), MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No. 18YJCZH054), Natural Science Foundation of Guangdong Province (Nos. 2018A030307033, 2018A0303130274), Social Science Foundation of Guangdong Province (No. GD18CFX06) and Special Innovation Projects of Universities in Guangdong Province (No. KTSCX205).


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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.College of ComputerNational University of Defense TechnologyChangshaChina
  2. 2.School of Information Science and EngineeringShaoguan UniversityShaoguanChina

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