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Multi-attributes Decision-making Based on the Flexible Linguistic Expressions TOPSIS Method

Various linguistic expression have been presented for improving the flexibility of preference expression in multi-attributes decision-making (MADM). A more flexible method, flexible linguistic expressions (FLE), were presented in decision-making (DM). Hence, FLEs and TOPSIS (FLE-TOPSIS) was proposed to rank alternatives. In FLE-TOPSIS, FLE is utilized to express decision makers’ preference information and we present a optimization model with minimum preference loss that is used to carry out normalized operator. After positive-ideal solution (PIS) and negative-ideal solution (NIS) were derived from normalized FLE, we define a closeness coefficient for determining alternatives ranking. Finally, a comparative analysis is presented to verify our proposal.