A hybrid intuitionistic fuzzy multi-criteria group decision making approach for supplier selection

Due to the increasing competition of globalization, selection of the most appropriate supplier is one of the key factors for asupply chain management’s success. Due to conflicting evaluations and insufficient information about the criteria, Intuitionisticfuzzy sets (IFSs) considered as animpressive tool and utilized to specify the relative importance of the criteria. The aim of this paper is to develop a new approach for solving the decision making processes. Thusan intuitionistic fuzzy multi-criteria group decision making approach is proposed. Interval-valued intuitionistic fuzzy ordered weighted aggregation (IIFOWA) is utilized to aggregate individual opinions of decision makers into a group opinion. A linear programming model is used to obtain the weights of the criteria.Then acombined approach based onGRAand TOPSIS method is introduced and applied to the ranking and selection of the alternatives. Finally a numerical example for supplier selection is given to illustrate the feasibility and effectiveness of the proposed method. A combined method based on GRA and TOPSIS associated with intuitionistic fuzzy set has enormous chance of success for multi-criteria decision-making problems due to containing vague perception of decision makers’ opinions. Therefore, in future, intuitionistic fuzzy set can be used for dealing with uncertainty in multi-criteria decision-making problems such as project selection, manufacturing systems, pattern recognition, medical diagnosis and many other areas of management decision problems

A Multi-criteria Picture Fuzzy Decision-making Model for Green Supplier Selection based on Fractional Programming

Due to the increasing complexity in green supplier selection, there would be some important issues for expressing inherent uncertainty or imprecision of decision makers’ cognitive information in decision making process. As an extension of intuitionistic fuzzy sets (IFSs) and neutrosophic sets (NSs), picture fuzzy sets (PFSs) can better model and represent the hesitancy and uncertainty of decision makers’ preference information. In this study, an attempt has been made to present a multi-criteria picture fuzzy decision-making model for green supplier selection based on fractional programming. In this approach, the ratings of alternatives and weights of criteria are represented by PFSs and IFSs, respectively. Based on the available information, some pairs of fractional programming models are derived from the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and the proposed biparametric picture fuzzy distance measure to determine the relative closeness coefficient intervals of green suppliers, which are aggregated for the criteria to generate the ranking order of all green suppliers by computing their optimal degrees of membership based on the ranking method of interval numbers. Finally, an example is conducted to validate the effectiveness of the proposed multi-criteria decision making (MCMD) method

NEW DISSIMILARITY MEASURES ON PICTURE FUZZY SETS AND APPLICATIONS

The dissimilarity measures between fuzzy sets/intuitionistic fuzzy sets/picture fuzzy sets are studied and applied in various matters. In this paper, we propose some new dissimilarity measures on picture fuzzy sets. This new dissimilarity measures overcome the restrictions of all existing dissimilarity measures on picture fuzzy sets. After that, we apply these new measures to the pattern recognition problems. Finally, we introduce a multi-criteria decision making (MCDM) method that used the new dissimilarity measures and apply them in the supplier selection problems

A complex proportional assessment method for group decision making in an interval-valued intuitionistic fuzzy environment

Multi-criteria decision making is an implicational field that concerns with selecting or designing the best scenarios among a finite set of scenarios based on a finite set of criteria. Different methods and techniques for handling this issue have been proposed. Complex proportional assessment is an analytical tool for solving multi-criteria decision making problems. Originally, the COPRAS method has been developed for decision making under a deterministic environment. Since uncertainty is an unavoidable property of decision making due to a lack of knowledge, this paper suggests an extended form of the COPRAS method used for group decision making problems in an uncertain environment where such uncertainty is captured through a generalized form of fuzzy sets - the so called interval valued intuitionistic fuzzy sets. An algorithmic scheme for the COPRAS-IVIF method has been introduced thus examining its application with reference to two numerical examples. It seems that the recommended framework of COPRAS-IVIF can be satisfactorily implemented in decision making problems under ambiguous and ill-defined conditions

Application of Mathematical Modeling in Multi Criteria Decision Making Process: Intuitionistic Fuzzy PROMETHEE

In this paper, the intuitionistic fuzzy PROMETHEE method is explained in detail and an original application has been made. The aim of the paper is to bring innovation to the evaluation system in the field of education by using the intuitionistic fuzzy PROMETHEE method. The advantages of using the PROMETHEE method, which is one of the many methods used in multi-criteria decision-making problems, in the intuitionistic fuzzy sense are explained in detail. Intuitionistic fuzzy PROMETHEE is a method that attracts our attention thanks to its benefits such as allowing the researcher to observe the positive and negative rankings simultaneously, expressing the degree of hesitation, changing the significance weights of the criteria, and using different methods when identifying the significance levels for each criterion, putting the degree of hesitation of significance weights into action, and enabling decision-makers, who are given the opportunity to use different criteria types and different criteria types for alternatives and criteria, to establish a unique system; moreover, the method also provides us numerous advantages while using it in our application area. It is of great importance for decision-makers to determine the specific importance level for each criterion. In this paper, controlled sets are used to express the importance of the criteria in the form of intuitionistic fuzzy values. The intuitionistic fuzzy-based PROMETHEE algorithm, aiming to contribute to the education system by examining the factors affecting the students' achievement, is a unique algorithm, and it is the first to shed light on various researchers

Technology assessment with IF-TOPSIS: An application in the advanced underwater system sector

Technologies are pivotal for firms' success, but also resource consuming. Therefore, managers have to assess and select technologies carefully in order to allocate resources on the most promising ones, grounding their decisions on adequate sets of criteria on which experienced people can express their opinion.This work proposes an application of Multi Criteria Decision Aids to technology assessment, where Decision Support Systems offer an effective support for evaluating technology impact on firms' success, building on experts' judgments.The method is based on a peer-based modification to Intuitionistic Fuzzy multi-criteria group decision making with TOPSIS method (peer IF-TOPSIS). A case study in which this methodology is applied to a company operating in the military sector (Advanced Underwater System) is also presented.Besides the empirical proof of the method's suitability and value in assisting managers in their decision, the paper's contributions are both methodological and theoretical. Methodologically, while allowing a peer-based voting procedure, the method enhances the consensus in the firm and limits the possible biases that a supra-decision maker could introduce. Theoretically, the set of proposed criteria includes many facets of the assessment problem, and avoids being tailored to the investigated technological field, so enhancing its generalizability