Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (6): 1192-1201.doi: 10.21629/JSEE.2019.06.13

• Systems Engineering • Previous Articles     Next Articles

Optimized interval 2-tuple linguistic aggregation operator based on PGSA and its application in MAGDM

Mengting ZONG1(), Tian SHEN2,*(), Xi CHEN1()   

  1. 1 School of Business, Nanjing University, Nanjing 210000, China
    2 School of Education, Nanjing University of Traditional Chinese Medicine, Nanjing 210000, China
  • Received:2018-07-09 Online:2019-12-20 Published:2019-12-25
  • Contact: Tian SHEN;;
  • About author:ZONG Mengting was born in 1991. She is currently a Ph.D. candidate at the Department of Business School, Nanjing University. Her research interests include group decision making, social network analysis, social computing experiments and digital innovation. E-mail:|SHEN Tian was born in 1978. She is a Ph.D. and an associate professor in Nanjing University of Traditional Chinese Medicine. Her research interests include medical services management, and simulation systems. E-mail:|CHEN Xi was born in 1977. He is a Ph.D. and a professor in Nanjing University. His research interests include information management, big data analysis and electronic business. E-mail:
  • Supported by:
    the National Natural Science Foundation of China(71771118);the National Natural Science Foundation of China(71471083);the Ministry of Education Humanities and Social Sciences Foundation of China(18YJCZH146);the Nanjing University Double First-Class project;This work was supported by the National Natural Science Foundation of China (71771118; 71471083), the Ministry of Education Humanities and Social Sciences Foundation of China (18YJCZH146), and the Nanjing University Double First-Class project


This study proposes a multiple attribute group decision-making (MAGDM) approach on the basis of the plant growth simulation algorithm (PGSA) and interval 2-tuple weighted average operators for uncertain linguistic weighted aggregation (ULWA). We provide an example for illustration and verification and compare several aggregation operators to indicate the optimality of the assembly method. In addition, we present two comparisons to demonstrate the practicality and effectiveness of the proposed method. The method can be used not only to aggregate MAGDM problems but also to solve multi-granularity uncertain linguistic information. Its high reliability, easy programming, and high-speed calculation can improve the efficiency of ULWA characteristics. Finally, the proposed method has the exact characteristics for linguistic information processing and can effectively avoid information distortion and loss.

Key words: multiple attribute group decision making (MAGDM), interval 2-tuple, plant growth simulation algorithm (PGSA), weighted Steiner point