Optimized intervaI 2-tupIe Iinguistic aggregation operator based on PGSA and its appIication in MAGD

• 作 者: ZONG Mengting SHEN Tian CHEN Xi
• 机 构: School of Business, Nanjing University, Nanjing 210000, China“,”School of Education, Nanjing Univers
• 出 处: 系统工程与电子技术（英文版）
• 发表日期: 2019年6期
• 关键词: muItipIe attribute group decision making (MAGDM) in-tervaI 2-tupIe pIant growth

This study proposes a muItipIe attribute group decision-making (MAGDM) approach on the basis of the pIant growth si-muIation aIgorithm (PGSA) and intervaI 2-tupIe weighted average operators for uncertain Iinguistic weighted aggregation (ULWA). We provide an exampIe for iIIustration and verification and com-pare severaI aggregation operators to indicate the optimaIity of the assembIy method. In addition, we present two comparisons to demonstrate the practicaIity and effectiveness of the proposed method. The method can be used not onIy to aggregate MAGDM probIems but aIso to soIve muIti-granuIarity uncertain Iinguistic in-formation. Its high reIiabiIity, easy programming, and high-speed caIcuIation can improve the efficiency of ULWA characteristics. FinaIIy, the proposed method has the exact characteristics for Iin-guistic information processing and can effectiveIy avoid information distortion and Ioss.