Informatica

Existing fuzzy inference systems are generally based on ordinary fuzzy sets, which do not let the second and third dimensions of the other fuzzy sets extensions to be employed. This paper suggests a decision-making approach by utilizing the fuzzy inference systems (FIS) based on spherical fuzzy sets (SFS). We prefer spherical fuzzy sets to consider the indecision degree together with membership and non-membership degrees in the proposed FIS. During the defuzzification of SF inference system, the indecision degree is distributed over membership and non-membership degree in balance regarding to indecision degree by using a special transformation function. By applying the proposed approach on FIS, it aims to cover hesitancies and uncertainties caused by insufficient assessments of the decision makers more effectively. The proposed decision-making approach is tested with a real-world application in the field of maintenance work order prioritization for scheduling. Finally, the result of the suggested approach based on SFS is compared with the risk assessment matrix technique (RAM) existing in the literature and Picture Fuzzy Inference Systems (PiFIS). It is observed that the proposed Spherical Fuzzy Inference System (SFIS) is more efficient than RAM and PiFIS methods.

Picture fuzzy sets (PFSs) utilize the positive, neutral, negative and refusal membership degrees to describe the behaviours of decision-makers in more detail. In this article, we expound the application of extended TODIM based on cumulative prospect theory under picture fuzzy multiple attribute group decision making (MAGDM). In addition, we adopt Information Entropy, which is used to ascertain the weighting vector of attributes to improve the availability of the TODIM method. At last, we exercise the improved TODIM into a numerical case for super market location and testify the effectiveness of this new method by comparing its results with other methods’ results.

As an extension of intuitionistic fuzzy sets, picture fuzzy sets can deal with vague, uncertain, incomplete and inconsistent information. The similarity measure is an important technique to distinguish two objects. In this study, a similarity measure between picture fuzzy sets based on relationship matrix is proposed. The new similarity measure satisfies the axiomatic definition of similarity measure. It can be testified from a numerical experiment that the new similarity measure is more effective. Finally, we apply the proposed similarity measure to multiple-attribute decision making.

Green supplier selection has recently become one of the key strategic considerations in green supply chain management, due to regulatory requirements and market trends. It can be regarded as a multi-criteria group decision-making (MCGDM) problem, in which a set of alternatives are evaluated with respect to multiple criteria. MCGDM methods based on Analytic Hierarchy Process (AHP) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) are widely used in solving green supplier selection problems. However, the classic AHP must conduct large amounts of pairwise comparisons to derive a consistent result due to its complex structure. Meanwhile, the classic TOPSIS only considers one single negative idea solution in selecting suppliers, which is insufficiently cautious. In this study, an improved TOPSIS integrated with Best-Worst Method (BWM) is developed to solve MCGDM problems with intuitionistic fuzzy information in the context of green supplier selection. The BWM is investigated to derive criterion weights, and the improved TOPSIS method is proposed to obtain decision makers’ weights in terms of different criteria. Moreover, the developed TOPSIS-based coefficient is used to rank alternatives. Finally, a green supplier selection problem in the agri-food industry is presented to validate the proposed approach followed by sensitivity and comparative analyses.

Compared to fuzzy numbers, intuitionistic fuzzy numbers provide greater opportunities for solving complex decision-making problems, especially when they are related to ambiguities, uncertainties and vagueness. However, their use is more complex, especially when it comes to ordinary users. Therefore, in this paper an approach adopted for evaluating alternatives on the basis of a smaller number of some more complex evaluation criteria is proposed. The approach is based on the use of linguistic variables, triangular intuitionistic fuzzy numbers, and the Hamming distance. At the end, a case study of hotels’ websites evaluation is given to demonstrate the practicality and effectiveness of the proposed approach, together with its limitations and weaknesses. Additionally, a new procedure for ranking intuitionistic fuzzy numbers is proposed and its use is verified.