A hesitant fuzzy multiple attribute decision making method based on linear programming and TOPSIS*

Hesitant fuzzy set (HFS) provides an effective tool in dealing with decision making situation when only some values of a membership are possible for an alternative on certain attribute. In this paper, we propose a method based on linear programming and TOPSIS to solve the multiple attribute decision making (MADM) problem with partially known attribute weight information under hesitant fuzzy environment. To begin with, we present a linear programming model for assessing objective attribute weights from the decision making matrix and partially known attribute weight information. Moreover, we utilize the weighted correlation coefficient values between every alternative and the positive ideal point to rank all the alternatives based on TOPSIS. Furthermore, a numerical example is utilized to validate the MADM method proposed in this paper.