Abstract
In some multi-attribute decision-making (MADM) models studying attributes’ interactive phenomena is very important for the minimizing decision risks. Usually, the Choquet integral type aggregations are considered in such problems. However, the Choquet integral aggregations do not consider all attributes’ interactions; therefore, in many cases, when these interactions are revealed in less degree, they do not perceive these interactions and their utility in MADM problems is less useful. For the decision of this problem, we create the Choquet integral-based new aggregation operators’ family which considers all pair interactions between attributes. The problem under the discrimination q-rung picture linguistic and q-rung orthopair fuzzy environments is considered. Construction of a 2-order additive fuzzy measure (TOAFM) involves pair interaction indices and importance values of attributes of a MADM model. Based on the attributes’ pair interactions for the identification of associated probabilities of a 2-order additive fuzzy measure, the Shapley entropy maximum principle is used. The associated probabilities q-rung picture linguistic weighted averaging (APs-q-RPLWA) and the associated probabilities q-rung picture linguistic weighted geometric (APs-q-RPLWG) aggregation operators are constructed with respect to TOAFM. For an uncertainty pole of experts’ evaluations on attributes regarding the possible alternatives, the associated probabilities of a fuzzy measure are used. The second pole of experts’ evaluations as arguments of the aggregation operators by discrimination q-rung picture linguistic values is presented. Discrimination q-rung picture linguistic evaluations specify the attribute’s dominant, neutral and non-dominant impacts on the selection of concrete alternative from all alternatives. Constructed operators consider the all relatedness between attributes in any consonant attribute structure. Main properties on the rightness of extensions are showed: APs-q-RPLWA and APs-q-RPLWG operators match with q-rung picture linguistic Choquet integral averaging and geometric operators for the lower and upper capacities of order two. The conjugation among the constructed operators is also considered. Connections between the new operators and the compositions of dual triangular norms (Tp,Spq) and (Tmin,Smax) are also constructed. Constructed operators are used in evaluation of a selection reliability index (SRI) of candidate service centers in the facility location selection problem, when small degree interactions are observed between attributes. In example MADM, the difference in optimal solutions is observed between the Choquet integral aggregation operators and their new extensions. The difference, however, is due to the need to use indices of all interactions between attributes.
Highlights
The associated probabilities q-rung picture linguistic weighted averaging (APs-q-RPLWA) and the associated probabilities q-rung picture linguistic weighted geometric (APsq-RPLWG) aggregation operators are constructed with respect to TOAFM
The novelty is that the Choquet type aggregations do not consider all pair interactions; in many cases, when these interactions are revealed in less degree, they do not perceive these interactions and their utility in multi-attribute decision-making (MADM) problems is less useful than the new aggregation operators’ family developed in the article
This is explained by the fact that the transformation from experts q-ROF evaluations to q-RPL evaluations resulted in the expansion of information in the linguistic variables environment, and this gave an alternative decision—the opened service center with a higher selection reliability index (SRI) cs5 instead of cs4
Summary
Today we often touch with multi-attribute (criteria) decision-making (MADM/MCDM). models, methods or software to solve practical important complex problems in medicine, economics, technologies, business and others. It may happen that a DM provides such data for certain attribute that the aforementioned sum is greater than 1 (μ + υ > 1) To cope with such a case, Yager [6,7] introduced the concept of the Pythagorean fuzzy set (PFS) as a generalization of IFS, where a Pythagorean fuzzy number (PFN) (μ, υ) has a weaker constraint—the sum of squared degrees of membership and non-membership satisfies the inequality μ2 + υ2 ≤ 1. The new concept of q-RPLS fully describes both q-ROFS and PIFS concepts and, reflects the qualitative and quantitative assessments of DMs. Subsequently, the study of aggregation operators using q-RPLS information [24] in interactive/correlated attributes decision-making models began to develop
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