Incomplete pythagorean fuzzy preference relation for subway station safety management during COVID-19 pandemic

Zhenyu Zhang; Huirong Zhang; Lixin Zhou; Yong Qin; Limin Jia

doi:10.1016/j.eswa.2022.119445

Incomplete pythagorean fuzzy preference relation for subway station safety management during COVID-19 pandemic

Expert Syst Appl. 2023 Apr 15:216:119445. doi: 10.1016/j.eswa.2022.119445. Epub 2022 Dec 20.

Authors

Zhenyu Zhang¹, Huirong Zhang², Lixin Zhou³, Yong Qin⁴, Limin Jia⁴

Affiliations

¹ School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China.
² School of Labor Relationship, Shandong Management University, Jinan 250357, China.
³ Business School, University of Shanghai for Science and Technology, Shanghai 200093, China.
⁴ State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China.

Abstract

Completing the Pythagorean fuzzy preference relations (PFPRs) based on additive consistency may exceed the defined domain. Therefore, we develop a group decision-making (GDM) method with incomplete PFPRs. Firstly, sufficient conditions for the expressibility of estimated preference values in PFPRs based on additive consistency are presented. Next, the correction algorithm is developed to correct the inexpressible elements in incomplete PFPRs. Then, a GDM method based on incomplete PFPRs is proposed to determine the objective weights of decision-makers. Finally, an example of subway station safety management during COVID-19 is selected to illustrate the applicability of the developed GDM method. The results show that the developed GDM method effectively identifies the crucial risk factor in subway station safety management and has better performance in terms of computational time complexity than the multiplicative consistency method.

Keywords: Additive consistency; COVID-19; Pythagorean fuzzy preference relation (PFPR); Subway station safety management.