Multicriteria decision-making based on linguistic label vague sets

For multicriteria decision-making based on vague sets (MDMV), the uncertain circumstance sometimes can not provide the precise numerical values for both the grade of the truth-membership and that of the false-membership of an object in the vague sets. In order to solve the problem, this paper puts forward the multicriteria decision-making based on linguistic label vague sets (MDMLLV). In MDMLLV, firstly, the information table is constituted; secondly, the characteristics of alternatives are presented by linguistic label vague (LLV) sets; thirdly, the degrees to which alternatives satisfy and do not satisfy the decision-maker´s requirement are measured by the evaluation functions, fourthly, the ratings of all alternatives are represented by the score functions; and finally, the order of all alternatives is determined by the dominant relation of linguistic labels. The result of our simulation example shows that MDMLLV is sometimes more practical and feasible than MDMV.