An Aspiration-Based Approach for Qualitative Decision-Making With Complex Linguistic Expressions

Decisions are usually made based on not only the performances of alternatives but also are implied by how the performances satisfy the decision makers' aspiration levels. This paper presents a linguistic aspiration-based solution to qualitative decision-making (QDM) where the aspiration levels and performances can be expressed by complex linguistic expressions (CLEs) such as hesitant fuzzy linguistic term sets and linguistic terms with weakened hedges. The proposed approach can deal with complex problems, which involve multi-criteria, multi-groups of experts, and multi-granular linguistic information. Based on the conventional aspiration-based approaches, the value function is defined by the probability of a CLE achieving its linguistic aspiration level. The performance of the proposed QDM approach is then demonstrated by solving the problem regarding the provider evaluation and selection. The proposed approach extends the range of available natural linguistic expressions that can be considered and used by experts and emphasizes the role of linguistic aspiration levels in QDM.