4.5 Article

Work Resumption After Epidemic Using Three-Way Decisions

Journal

INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
Volume 23, Issue 3, Pages 630-641

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s40815-020-01006-5

Keywords

Work resumption; Three-way decisions (TWDs); Double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs); Entropy weight method

Funding

  1. Natural Science Foundation of China [71771155, 71971119]
  2. Collaborative Innovation Center of Audit Information Engineering and Technology, Nanjing Audit University, Nanjing, China [18CICA01]

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The study proposes a novel three-way decision method for making decisions on whether enterprises should resume work post-epidemic. The method involves describing enterprise attributes, calculating attribute weights using the entropy weight method, and ultimately making decision results based on minimizing losses.
After the epidemic, all enterprises are faced with the difficult decision about whether the enterprise should resume work and production immediately, which is related to the safety and development of enterprises. The three-way decisions offer a novel study perspective to solve this problem. Firstly, we describe some relevant attributes of the enterprise with double hierarchy hesitant fuzzy linguistic term sets, and construct double hierarchy hesitant fuzzy linguistic information systems for each enterprise. Secondly, we get the weights of attributes with the entropy weight method, and take the weighted aggregation of attributes information as the conditional probability that the enterprise is in a safe state. Next, we classify each enterprise according to its size. Considering the influence of different sizes of enterprises, we put forward the corresponding loss function matrix. Then we get the decision results about work resumption based on the principle of minimizing the loss, which demonstrates the practicability and effectiveness of our method. Finally, we compare the method proposed by us with the other method and discuss the advantages and limitations of our proposed method.

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