Fuzzy GRA Research Articles

Personal Information Security Risk Assessment for E-Waste Recycling Based on Fuzzy–GRA–TOPSIS and FMEA

Personal Information Security Risk Assessment for E-Waste Recycling Based on Fuzzy–GRA–TOPSIS and FMEA

Research on lean management and innovation capability evaluation of technological small and medium sized enterprises under probabilistic hesitant fuzzy sets

The lean management and innovation capability evaluation of technological small and medium sized enterprises is a classical multi-attributes group decision-making (MAGDM). Recently, the probabilistic hesitant fuzzy sets (PHFSs) have been extended to apply in many fields. However, the existing models don’t evaluate the alternative considering the psychological factors. Thus, in this paper, an extended probabilistic hesitant fuzzy grey relational analysis (PHF-GRA) method is proposed to reduce the restrictions of GRA method by combining with cumulative prospect theory (CPT), considering the psychological preference. In addition, the PHFSs assigns probability values to different degrees of hesitancy, which shows its superiority in complex environment. At the same time, the weight vectors of each attribute are calculated by the entropy values of different foreground decision elements. Then, probabilistic hesitant fuzzy GRA (PHF-GRA) model based on CPT model is constructed for MAGDM under PHFSs. Finally, a practical example study for lean management and innovation capability evaluation of technological small and medium sized enterprises is constructed to validate the proposed GRA (PHF-GRA) model based on model CPT and some comparative studies are constructed to verify the applicability.

Application of fuzzy group decision-making selecting green supplier: a case study of the manufacture of natural laurel soap

The selection of suppliers alone is one of the most important competitive challenges facing organizations today. With today's increasing awareness and facing many significant environmental pressures, the process of selecting the right suppliers for green supply chain management is even more difficult for decision-makers. The process of developing and implementing decision-making tools seek to face these challenges is rapidly evolving, especially in a fuzzy environment whose data are incomplete. The purpose of this article is to investigate prospective green chain suppliers for a laurel soap producing company based on a framework using MCDA fuzzy technologies such as Fuzzy GRA, Fuzzy TOPSIS, and Fuzzy VIKOR. During this paper, a discussion of fuzzy set was discussed with Fuzzy MCDM. Within a realistic case study, where a comparison was made between the tools, and it was noted that the results were consistent between the two tools Fuzzy TOPSIS and Fuzzy GRA, and the arrival of similar results and a slight difference with results was observed in Fuzzy VIKOR interpreted. The most detailed analyses were conducted on distance measurements, linguistic variables, assembly functions, and confusion processing. This study introduces the Fuzzy MCDM method to help researchers choose a more effective approach for green supplier selection and the conclusions and other study directions are offered toward the conclusion of the paper.

A Grey Simulation-Based Fuzzy Hierarchical Approach for Diagnosing Healthcare Service Quality

This study aims to assess and rank the service quality of the healthcare system utilizing a Fuzzy Analytical Hierarchical Process (Fuzzy AHP) and Grey Relational Analysis (Fuzzy GRA) technique. In this study, the six primary characteristics of healthcare service quality, comprising Tangibles (A), Healthcare Staff (B), Responsiveness (C), Relationships (D), Support Service (E), and Accessibility (F), are examined through a case study of 20 private and public hospitals in Hanoi, Vietnam. The weighting results of Fuzzy AHP technique indicated that Responsiveness (C) has the highest ranking, followed by Relationships (D) and Healthcare Staff (B). Meanwhile, Tangibility has finally comprised the next priority for increasing satisfaction with the service quality in the healthcare industry. Additionally, the highest service quality rankings are top 5 private hospitals via the Fuzzy GRA approach. Notably, this proposed approach may be applied to a complex decision-making process, which often makes sense with subjective data or imprecise information.

Development of interval-valued fuzzy GRA with SERVPERF based on subjective and objective weights for evaluation of airline service quality: A case study of Korea low-cost carriers.

As the airline industry has become ever-more competitive and profitability more tenuous, airline service quality management has grown more important to airlines. Although many studies have focused on the evaluation of airline service quality, some common limitations need to be noted. First, traditional fuzzy logics were utilized to present linguistic variables as fuzzy numbers. However, precise quantification of lower and upper bounds with a single number is often difficult; thus, interval-valued fuzzy sets that represent the lower and upper bounds in the fuzzy number as an interval form should be applied instead. Second, while some studies have applied various multiple-criteria decision-making method [MCDM] and the service quality (SERVQUAL) method for evaluation of airline service quality, few have utilized grey relational analysis (GRA, a simple and data-driven MCDM method applicable to environments with incomplete information) and the service performance (SERVPERF), a performance-based measure that can resolve the ambiguity issue of the expectations construct in SERVQUAL. Third, extant studies dealing with the issue of weighting criteria in the evaluation of airline service quality have focused only on either subjective or objective weights, though weighting criteria based on a combined objective/subjective approach would be much better than those just considering the subjective approach. The present study endeavored to fill these literature gaps by developing, for evaluation of airline service quality, interval-valued fuzzy GRA with SERVPERF based on both subjective and objective weights. It contributes to the field by incorporating the 22 criteria from SERVPERF to effectively account for the various characteristics of airline service. Additionally, it is the first study to utilize interval-valued fuzzy GRA together with a novel technique that combines a subjective/objective weighting method for integration of objective decision-matrix-derived information with subjective decision-maker preferences. The supplemental empirical case study of airline service evaluation, further, provides researchers and practitioners with a means of better understanding the proposed approach in the practical perspectives.

A novel approach for failure mode and effect analysis in propeller shaft manufacturing industry using fuzzy analytic hierarchy process and GRA VIKOR

The present study develops the evaluation model based on FMEA and AHP integrated with GRA VIKOR under fuzzy environment to evaluate the greatest risk for processes in the production of dust cap assembly in the propeller shaft manufacturing industry. Three risk factors S, O, D and their weights are treated as fuzzy triangular linguistic variables to eliminate the risk for production. FAHP is used to compute the weights of S, O, D whereas GRA VIKOR is used to obtain the final ranking of a risk alternative. Here, the risk factors and their weights are treated as fuzzy triangular linguistic variables for eliminating the risk of subjective quantification and similarity of risk priority number (RPN). Among the various failures, drawing dimension failure and blanking of blank failure are obtained as the most serious failure modes using fuzzy GRA VIKOR.

A novel approach for failure mode and effect analysis in propeller shaft manufacturing industry using fuzzy analytic hierarchy process and GRA VIKOR

A novel approach for failure mode and effect analysis in propeller shaft manufacturing industry using fuzzy analytic hierarchy process and GRA VIKOR

Using a multi-criteria decision making approach to select the optimal freeway rout (case study: Isfahan-Shiraz Freeway)

Road construction problems are one of the important factors in countries. The effects of multiple parameters on the decision making process to determine the optimal route have made this choice a specialised issue for decision-makers. In this regard, this paper aims to select the optimal route for Isfahan-Shiraz freeway using MADM approaches. For this purpose, in order to weight and select the optimal route, the extended dynamic fuzzy GRA method is used. The results show that road longevity, views of the NGOs, route integrity and ease of tracking are identified as the highest-weighted criteria in the prioritisation of the route variant. To evaluate the validity of the results of the GRA method, the problem is examined by using the, COPRAS-IVIF, ARAS-IVTF, WASPAS-IVIF, TOPSIS-IVIF and MULTIMOORA-IVIF methods. In addition, route 3 that takes priority over others is also chosen, in practice, as the main basis for the work.

Investigating ideal-solution based multicriteria decision making techniques for sustainability evaluation of urban mobility projects

Confronted with negative environmental impacts, rising fuel costs and increasing congestion, many cities are implementing sustainable mobility measures to improve the flow of passenger and goods. Examples of these measures are use of public transport, cycling, walking, energy efficient vehicles, biofuels. The challenge before transport decision makers is which one(s) to choose for implementation as often there is no or limited quantitative data available on the subject. Moreover, the context of each city, its geographic and transport conditions restrict the generalization of results obtained in experienced cities. In this paper, we are investigating application of ideal solution based multicriteria decision making (MCDM) techniques namely fuzzy TOPSIS, fuzzy VIKOR, and fuzzy GRA for sustainability evaluation of urban mobility projects. A real application for city of Luxembourg is provided. Three projects are evaluated namely implementation of a new tramway in the city center of Luxembourg, re-organization of existing bus lines in the city to perform optimized service, and implementation of electric vehicle car-sharing stations in the city. Sensitivity analysis is performed to determine the influence of input parameters on modeling results.The proposed work is one of the first few works to investigate application of ideal-solution based multicriteria decision making techniques for sustainability evaluation of urban mobility projects under uncertainty. Besides, the best alternative is selected using veto thereby overcoming the limitations of single MCDM methods.

An Integrated TOPSIS, GRA and VIKOR Based on Interval Type-2 Fuzzy Method to Improve Customer Satisfaction in Public Transportation

Recently, multi-criteria decision making problems with interval type-2 fuzzy methods have received increasing attention both from researchers and practitioners. In this study, an interval type-2 fuzzy TOPSIS and GRA based VIKOR method is proposed for the evaluation of the customer satisfaction in all the transportation modes in Istanbul (metro, bus and bus rapid transit). Furthermore, the interval type-2 fuzzy TOPSIS method is also utilized to solve the problem. An online survey is conducted to investigate factors affecting public transport users’ satisfaction with the service. Data is collected from 323 public transport users in Istanbul. As a result, an interval type-2 fuzzy multi-criteria decision making method has been proposed for the evaluation of customer satisfaction in public transportation. The performances of various multi-criteria decision making methods are also compared with each other with a view to exploring the effectiveness and flexibility of proposed method and interval type-2 fuzzy TOPSIS method. The results show that the proposed method is reliable and practical for evaluate problems and other MCDM problems.

Selection of optimal variant route based on dynamic fuzzy GRA

Selection of optimal variant route based on dynamic fuzzy GRA

Failure mode and effect analysis using fuzzy analytic hierarchy process and GRA TOPSIS in manufacturing industry

Failure mode and effect analysis using fuzzy analytic hierarchy process and GRA TOPSIS in manufacturing industry

Failure mode and effect analysis using fuzzy analytic hierarchy process and GRA TOPSIS in manufacturing industry

In the manufacturing industry, system failures may cause to personnel and infrastructure damages to the organisation which leads to loss in production. FMEA is a widely used engineering technique to improve product quality, reliability and eliminate known and/or potential failures. The present study develops evaluation model based on FMEA and FAHP integrated with combination of TOPSIS and GRA to valuate greatest risk in the processes for production of automotive dust cap in manufacturing industry. FAHP is used to compute the weights whereas fuzzy TOPSIS is used to obtain the final ranking. Among the various failure, blanking of blank failure mode is ranked first in the priority order to make an attention followed by the drawing dimension failure > window cutting failure > final inspection of dimension failure > packing (short excess quantity) failure > hole size failure > packing (damage in pack) failure > dispatch failure > plating failure.

An extended fuzzy TOPSIS–GRA method based on different separation measures for green logistics service provider selection

In this paper, first, the criteria that make logistics service providers more “green” are determined as: cooperation with customer’s company and its customer, green government regulations, environmental management system, green process design, reduction in energy consumption and green network design. The criteria weights are determined by fuzzy AHP, based on expert opinions. Then, a new method is proposed, which is the combination of fuzzy TOPSIS and GRA, and used to evaluate green 3PLs based on different separation measures, as an extension, using trapezoidal fuzzy numbers. Five Turkish 3PLs serve in Istanbul are selected in order to apply a case study to show the applicability of the proposed method. Finally, the proposed method is verified with respect to different resolving coefficient values and separation measures and also compared with fuzzy TOPSIS and fuzzy VIKOR method results. Different multi-criteria decision-making methods can be applied and compared to check validity of our results for future studies. The proposed method can also be implemented to 3PLs in other countries.

Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry

The incorporation of environmental criteria into the conventional supplier selection practices is essential for organizations seeking to promote green supply chain management. Challenges associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. The development and implementation of practical decision making tools that seek to address these challenges are rapidly evolving. This article contributes to this knowledge area by comparing the application of three popular multi-criteria supplier selection methods in a fuzzy environment. The incorporation of fuzzy set theory into TOPSIS, VIKOR and GRA methods is thoroughly discussed. The methods are then utilized to complete a green supplier evaluation and selection study for an actual company from the agri-food industry. Our comparative analysis for this case study indicates that the three fuzzy methods arrive at identical supplier rankings, yet fuzzy GRA requires less computational complexity to generate the same results. Additional analyses of the numerical results are completed on the normalization functions, distance metrics, and aggregation functions that can be used for each method.

Collaboration partner selection for city logistics planning under municipal freight regulations

Collaboration planning among city logistics operators is important to achieve operational efficiency under municipal freight regulations such as access, sizing and timing restrictions etc. In this paper, we present a fuzzy BOCR–GRA approach for collaboration partner selection for city logistics planning under the presence of municipal freight regulations. A multi-step approach is proposed. In the first step, we identify collaboration partner evaluation criteria using BOCR framework. In the second step, linguistic assessment of criteria and alternatives (collaboration partners) is performed by a decision making committee. The linguistic data is treated via fuzzy triangular numbers for analytical processing. In the third step, alternatives are ranked using Gray Relational Analysis technique (GRA) and five BOCR scoring methods. The different alternative ranks are subject to veto and the alternative(s) with highest top ranks are considered for sensitivity analysis whereby we analyze the influence of changes in criteria weights and scoring methods on their ranks. If the rankings remain unchanged, then the veto retained alternative(s) are declared as winner(s) and recommended for collaboration. A numerical application is provided.This is one of the first works to address the collaboration partner selection problem in the context of city logistics under limited or lack of quantitative data. A comprehensive set of criteria are proposed and the best solution is generated using veto role on various scores obtained from BOCR and fuzzy GRA, thereby eliminating any bias arising from method selection.

Evaluation and selection of emergency treatment technology based on dynamic fuzzy GRA method for chemical contingency spills

A robust scheme to address emergency pollution accident is becoming more and more important with the rise of the frequency and intensity of the emergency pollution accidents. Therefore, it is crucial to select an appropriate technology in an emergency response to chemical spills. In this study, an evaluation framework based on dynamic fuzzy GRA method has been developed to make forward optimum scheme for the selection of emergency treatment technology. Dynamic analysis and linguistic terms are used to evaluate alternatives to improve efficiency of emergency treatment procedures by addressing the vagueness and ambiguity in decision making. The method was then applied in a case study to evaluate emergency arsenic treatment technology and demonstrate its applicability and feasibility in emergency arsenic pollution under two scenarios associated with different arsenic levels. Therefore, not only the results can be used for selecting emergency treatment technology, but also help decision-makers identify desired decisions for contaminant mitigation with a quick response and cost-effective manner.