Abstract

In real decision making problems, it is always more natural for decision makers to use linguistic terms to express their preferences/opinions in a qualitative way among alternatives than to provide quantitative values. Additionally, many of these decision making problems are under uncertain environments with vague and imprecise information involved. Following the idea of Computing with Words (CWW) methodology, we propose in this paper a linguistic valued qualitative aggregation and reasoning framework for multi-criteria decision making problems, where a linguistic valued algebraic structure is constructed for modelling the linguistic information involved in multi-criteria decision making problems, and a linguistic valued logic based approximate reasoning method is developed to infer the final decision making result. This method takes the advantage of handling the linguistic information, no matter totally ordered or partially ordered, directly without numerical approximation, and having a non-classical logic as its formal foundation for decision making process.

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