Some novel decision making algorithms for intuitionistic fuzzy soft set

Article type: Research Article

Authors: Peng, Xindong^{; *}

Affiliations: School of Information Science and Engineering, Shaoguan University, Shaoguan, China

Correspondence: [*] Corresponding author. Xindong Peng, School of Information Science and Engineering,Shaoguan University, Shaoguan 512005,China. Tel.: +86-15889857163; E-mail: pengxindong@sgu.edu.cn.

Abstract:  This paper is designed to show deeper standpoints for dealing the decision making issues based on intuitionistic fuzzy soft set (IFSS). Firstly, we propose a novel definition and formula of similarity measure on intuitionistic fuzzy information, which can reserve more original judgment information. Afterwards, we present a combination weight that take the objective weight (obtained by grey system theory) and the subjective weight into consideration. Later, three intuitionistic fuzzy soft methods based on similarity measure, MABAC and EDAS are presented for dealing the decision making issues. Finally, the validity of methods are stated by some practical examples. The key characteristics of the developed methods have no strict requirements for decision data and possess a stronger ability in differentiating the best alternative.

Keywords: Similarity measure, combination weights, IFSS, MABAC, EDAS

DOI: 10.3233/JIFS-182768

Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1327-1341, 2019