A multihesitant fuzzy linguistic multicriteria decision-making approach for logistics outsourcing with incomplete weight information

In selecting logistics service providers, the evaluation criteria can be easily prioritized and possibly interrelated with each other, and the assessment of alternatives under qualitative criteria is usually accomplished by more than one decision maker. A novel multicriteria decision-making approach with multihesitant fuzzy linguistic term elements (MHFLTEs) based on the Heronian mean (HM) and prioritized average operators can effectively deal with the problems inherent in such a scenario. Multihesitant fuzzy linguistic term sets (MHFLTSs) were proposed on the basis of multihesitant fuzzy sets (MHFSs) and hesitant fuzzy linguistic sets (HFLSs), where each MHFLTE can contain nonconsecutive and repeated linguistic terms. Using MHFLTEs, one decision maker can provide one or several consecutive linguistic terms in evaluating an alternative under one specific criterion, different decision makers' evaluation values can be collected, and the frequency of a linguistic term in the evaluation information can accord with reality. This paper revises the basic operations and comparison method for MHFLTEs on the basis of the originals and defines some multihesitant fuzzy linguistic HM operators for MHFLTEs to deal with problems in which weight information cannot be accurately established for criteria, but their priorities can be provided in groups or without groups. Finally, the validity and effectiveness of the proposed approach are demonstrated through an illustration of a logistics outsourcing problem and a comparison analysis.