Group decision-making strategy based on aggregation operators of linguistic confidence interval neutrosophic numbers in a linguistic neutrosophic multivalued scenario

In the scenario of linguistic neutrosophic multivalued sets (LNMSs), LNMS can capture true, false, and indeterminate linguistic multivalued information and effectively represent group decision making information in multiple criteria group decision-making (MCGDM) issues. Therefore, the objective of this study is to develop an MCGDM strategy using linguistic confidence interval neutrosophic number (LCINN) trigonometric aggregation operators to effectively tackle MCGDM problems with periodicity in an LNMS scenario. To do so, this study first presents a transformation approach from LNMS to the linguistic confidence interval neutrosophic set to ensure the confidence level of linguistic term sequences (LTSs) in LNMS from the perspective of probability estimation and to address the operation issue between different LTS lengths. Next, the linguistic sine t-norm, cosine tconorm, and trigonometric operation laws of LCINNs are defined to include the periodic features of the sine and cosine functions. Then, the LCINN trigonometric weighted average and geometric operators are constructed to provide periodic aggregation tools for LCINNs in the LNMS scenario. Furthermore, an MCGDM strategy using the proposed aggregation operators is constructed to effectively tackle MCGDM problems with periodicity in LNMS scenarios. Finally, the constructed MCGDM strategy is applied to a choice case of energy storage technologies, and then its validity of the ranking results is presented by comparing it with the existing MCGDM methods in the scenarios of linguistic neutrosophic uncertain sets and LNMSs. In addition, the proposed strategy (no learning process) is simpler in the decision-making process than machine learning or artificial intelligence decisionmaking algorithms.