Selection of Coal Transportation Company Based on Fuzzy SWARA-COPRAS Approach

Background: Coal production and marketing enterprises can significantly reduce transportation costs and improve their competitiveness by choosing appropriate road transportation companies. Methods: Based on this, a trapezoidal fuzzy SWARA-COPRAS method is proposed to select coal transportation companies. The trapezoidal fuzzy SWARA method is used to determine the index weight of coal transportation companies. The ranking of coal transportation companies is determined using the trapezoidal fuzzy COPRAS method. Results: Taking a coal production and marketing enterprise in Hubei, China as an example, the application of the trapezoidal fuzzy SWARA-COPRAS method is illustrated, and the coal transportation companies are sorted and analyzed for sensitivity. Conclusions: Compared with the results of other methods, the effectiveness and practicability of the trapezoidal fuzzy SWARA-COPRAS method are verified.

Complex intuitionistic fuzzy soft SWARA - COPRAS approach: An application of ERP software selection

<abstract><p>In this manuscript, we propose an integrated framework based on COmplex PRoportional ASsessment and Step-wise Weight Assessment Ratio Analysis approach within the complex intuitionistic fuzzy soft (CIFS) context. This context is an ideal technique with complex fuzzy foundation that means to denote multi-dimensional data in a concise. In this framework, criteria weights are evaluated by the SWARA technique, and the ranking of alternatives is determined by the COPRAS method using CIFSs. Further, to illustrate the applicability of the presented technique, an empirical case study of ERP software selection problem is taken. A comparative study and sensitivity analysis is presented to verify the strength of the presented methodology.</p></abstract>

A New Entropy Measurement for the Analysis of Uncertain Data in MCDA Problems Using Intuitionistic Fuzzy Sets and COPRAS Method

In this paper, we propose a new intuitionistic entropy measurement for multi-criteria decision-making (MCDM) problems. The entropy of an intuitionistic fuzzy set (IFS) measures uncertainty related to the data modelling as IFS. The entropy of fuzzy sets is widely used in decision support methods, where dealing with uncertain data grows in importance. The Complex Proportional Assessment (COPRAS) method identifies the preferences and ranking of decisional variants. It also allows for a more comprehensive analysis of complex decision-making problems, where many opposite criteria are observed. This approach allows us to minimize cost and maximize profit in the finally chosen decision (alternative). This paper presents a new entropy measurement for fuzzy intuitionistic sets and an application example using the IFS COPRAS method. The new entropy method was used in the decision-making process to calculate the objective weights. In addition, other entropy methods determining objective weights were also compared with the proposed approach. The presented results allow us to conclude that the new entropy measure can be applied to decision problems in uncertain data environments since the proposed entropy measure is stable and unambiguous.

Fermatean Fuzzy CRITIC-COPRAS Method for Evaluating the Challenges to Industry 4.0 Adoption for a Sustainable Digital Transformation

Decision and policymakers are looking at the potential of Industry 4.0 smart technologies to create a green economy as the European Commission aims to deliver the European Green Deal by rethinking policies for clean energy supply. Industry 4.0 will eventually be applied to all aspects of life; however, it is necessary to identify the challenges to the adoption of Industry 4.0 for a sustainable digital transformation. In this vein, the present study aims to identify the challenges to the adoption of Industry 4.0 in fintech companies and to develop a novel Fermatean fuzzy CRITIC-COPRAS method to rank the identified challenges and evaluate the performance of companies concerning the weighted challenges based on three decision experts’ support. The results indicated that “difficulty in coordination and collaboration” is the most significant challenge to the adoption of Industry 4.0 out of the fourteen identified challenges, followed by “resistance to change” and “governmental support.” In addition, the superiority and efficiency of the proposed method were investigated through comparative analyses.

Supplier Selection of Shipbuilding Enterprises Based on Intuitionistic Fuzzy Multicriteria Decision

With the increasingly fierce competition in the global shipbuilding industry, shipbuilding enterprises need to maintain competitiveness and cope with rapid changes. In this case, shipbuilding enterprises need to establish effective supply chain management. Among them, choosing the right supplier is one of the most critical activities. The supplier selection of shipbuilding enterprises is considered a complex multicriteria decision-making (MCDM) problem that attracts much attention due to intuitionistic fuzzy sets to deal with possible imprecision and fuzziness in real life. Based on this, this paper proposes a new method based on the intuitionistic fuzzy SWARA (stepwise weight assessment ratio analysis) and COPRAS (complex proportional assessment) method to select shipbuilding enterprise suppliers which is a new research area. First of all, different weights are given to each expert evaluation result according to their position, educational background, and working years. The supplier index’s weight is determined based on the intuitionistic fuzzy SWARA method, and it is easy to understand and operate. The ranking of suppliers is determined by the intuitionistic fuzzy COPRAS method. This method considers all kinds of uncertainties and evaluates the utility index and the cost index of alternative suppliers. Finally, taking a shipbuilding enterprise as an example, applying the intuitionistic fuzzy SWARA-COPRAS method is illustrated. Compared with other methods and sensitivity analysis, it shows that the intuitionistic fuzzy multicriteria decision-making method is effective and stable in shipbuilding enterprises.

An integrated decision-making COPRAS approach to probabilistic hesitant fuzzy set information

The paper aims to present an integrated approach to solve the decision-making problem under the probabilistic hesitant fuzzy information (PHFI) features, which is an extension of the hesitant fuzzy set. The considered PHFI not only allows multiple opinions, but also associates occurrence probability to each opinion, which increases the reliability of the information. Motivated by these features of PHFI, an approach is presented to solve the decision problem with partial known information about the attribute and expert weights. In addition, an algorithm for finding some missing values in the preference information is presented and stated their properties. Afterward, the Hamy mean operator has been used to aggregate the different collective information into a single one. Also, we presented a COPRAS method to the PHFI for ranking the given alternatives. The presented algorithm has been demonstrated through a case study of cloud vendor selection and its validity has been revealed by comparing the approach results with the several existing algorithm results.

Operations on complex intuitionistic fuzzy soft lattice ordered group and CIFS-COPRAS method for equipment selection process

This paper introduces some new operations on complex intuitionistic fuzzy lattice ordered groups such as sum, product, bounded product, bounded difference and disjoint sum, and verifying its pertinent properties. The research exhibits the CIFS-COPRAS algorithm in a complex intuitionistic fuzzy soft set environment. This method was furthermore applied for the equipment selection process.

COPRAS METHOD FOR MULTIPLE ATTRIBUTE GROUP DECISION MAKING UNDER PICTURE FUZZY ENVIRONMENT AND THEIR APPLICATION TO GREEN SUPPLIER SELECTION

The green supplier selection (GSS) is a significant part in green supply chain management (GSCM). Choosing optimal green supplier can not only realize the sustainable development of enterprises, but also maximize the utilization rate of resources and diminish the negative effect of environmental issues, which conforms to the theme of green development. As a multiple attribute group decision-making (MAGDM) issue, selecting optimal green supplier is of vital important to enterprises. However, how to select the optimal supplier for enterprises is a great challenge. To handle this issue, a novel picture fuzzy COPRAS (COmplex PRoportional Assessment) method is devised. First, some necessary theories related to picture fuzzy sets (PFSs) are briefly reviewed. In addition, a method called CRITIC (Criteria Importance Though Intercrieria Correlation) is utilized to calculate criteria’s weights. Afterwards, the conventional COPRAS method is extended to the PFSs to calculate each alternative’s utility degree. At last, the designed method is exacted to an application which is related to GSS and there also conduct some comparative analysis to demonstrate the designed method’s superiority. The final results show that the proposed model can be utilized to decide the optimum green supplier.