Large-Scale Green Supplier Selection Approach under a Q-Rung Interval-Valued Orthopair Fuzzy Environment

As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee profit and sustainable development. Greensupplierselection(GSS),whichisakeysegmentofGSCM,hasbeeninvestigated to put forward plenty of GSS approaches

Novel possibility Pythagorean interval valued fuzzy soft set method for a decision making

We discuss the theory of possibility Pythagorean interval valued fuzzy soft set, possibility interval valued fuzzy soft set and define some related the operations namely complement, union, intersection, AND and OR. The possibility Pythagorean interval valued fuzzy soft sets are a generalization of soft sets. Notably, we showed DeMorgan’s laws that are valid in possibility Pythagorean interval valued fuzzy soft set theory. Also, we propose an algorithm to solve the decision making problem based on soft set method. To compare two possibilities Pythagorean interval valued fuzzy soft sets for dealing with decision making problems and find a similarity measure is obtained. Finally, an illustrative example is discussed to prove that they can be effectively used to solve problems with uncertainties.Publisher's Versio

Multi-perspective evaluation of integrated active cooling systems using fuzzy decision making model

As global median temperatures continue to rise, the demand for active cooling systems (ACs) is increasing. These systems are particularly prevalent in developed countries for maintaining comfort during hot weather. Various ACs technologies are available, and assessing their performance in multi-perspective settings is necessary to determine the best option for intended usage. This requires an evaluation platform for assessment. This paper presents a novel multi-criteria decision-making (MCDM) model based on a new integrated 2-tuple linguistic Pythagorean fuzzy-weighted zero-inconsistency (2 TLP-FWZIC) and modified 2-tuple linguistic Pythagorean fuzzy multi-attributive border approximation area comparison (2TLPF-MABAC). The former is used to determine the importance of assessment criteria, while the latter is employed for selecting the optimal ACs using the obtained weights. The first-level weighting results reveal that performance criteria were predominantly favored for assessment, with ‘energy performance’ acquiring the most significant weight (0.2487) among all performance criteria. In terms of ACs selection results, among the 20 tested and assessed systems, the ‘geothermal borehole electricity-based ACs’ obtained the highest score value (0.1296), while the ‘window packaged electricity-based ACs’ had the lowest score (-0.0515). The robustness of the results was confirmed through sensitivity analysis

Determine OWA operator weights using kernel density estimation

Some subjective methods should divide input values into local clusters before determining the ordered weighted averaging (OWA) operator weights based on the data distribution characteristics of input values. However, the process of clustering input values is complex. In this paper, a novel probability density based OWA (PDOWA) operator is put forward based on the data distribution characteristics of input values. To capture the local cluster structures of input values, the kernel density estimation (KDE) is used to estimate the probability density function (PDF), which fits to the input values. The derived PDF contains the density information of input values, which reflects the importance of input values. Therefore, the input values with high probability densities (PDs) should be assigned with large weights, while the ones with low PDs should be assigned with small weights. Afterwards, the desirable properties of the proposed PDOWA operator are investigated. Finally, the proposed PDOWA operator is applied to handle the multicriteria decision making problem concerning the evaluation of smart phones and it is compared with some existing OWA operators. The comparative analysis shows that the proposed PDOWA operator is simpler and more efficient than the existing OWA operator