Abstract
Advances in multi-attribute group decision making require the development of structures flexible enough to deal with unbalanced and multi-granular linguistic information. New distances between linguistic terms are needed to aggregate opinions and measure consensus among decision makers with different profiles. In this paper, firstly, based on the lattice structure of hesitant fuzzy linguistic terms sets, a perceptual-based distance able to capture differences between unbalanced linguistic assessments is developed. Secondly, a projected algebraic structure is defined to deal with multi-perceptual group decision-making contexts where each decision maker has its own qualitative reasoning approach. To this end, a methodology to aggregate unbalanced linguistic information based on different perceptual maps is developed. This methodology can also deal with different multi-granularity linguistic environments. Finally, through an illustrative example based on real data provided by the Andorra Government in a pilot test, the proposed framework is applied to classify and rank a set of secondary students according to their degree of entrepreneurial competency.
| Original language | English |
|---|---|
| Article number | 107662 |
| Pages (from-to) | 1-17 |
| Number of pages | 17 |
| Journal | Applied Soft Computing Journal |
| Volume | 111 |
| DOIs | |
| Publication status | Published - Nov 2021 |
Keywords
- Consensus measures
- Hesitant fuzzy linguistic term sets
- Linguistic modelling
- Multiple-attribute group decision-making
- Unbalanced linguistic term sets
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