Fuzzy Multi-criteria Decision-making Techniques Research Articles

A Hybrid Approach for Sustainable and Resilient Farmer Selection in Food Industry: Tunisian Case Study

This paper presents an innovative approach for supplier selection (SS) within the Tunisian dairy industry, with a specific focus on sustainability and resilience. The proposed method is a hybrid model that integrates multi-criteria decision-making (MCDM) with fuzzy logic. Initially, twelve distinct criteria are identified, categorized into social, environmental, economic, and resilience indexes through a combination of literature review and expert input. To establish the importance of these criteria, a fuzzy analytic hierarchy process (FAHP) is employed to calculate their weights. These weights are then integrated into a new method called fuzzy multi-attribute border approximation area comparison (FMABAC) to rank the suppliers. The methodology aims to provide decision-makers with a more intuitive means of expressing their preferences and evaluating supplier criteria, ultimately identifying the most effective dairy farmers. The research concludes by evaluating the results through two sensitivity analyses: one involving varying criteria weights and the other involving a comparative assessment with alternative fuzzy MCDM techniques.

Bipolar Fuzzy Multi-Criteria Decision-Making Technique Based on Probability Aggregation Operators for Selection of Optimal Artificial Intelligence Framework

Artificial intelligence (AI) frameworks are essential for development since they offer pre-built tools and libraries that speed up and simplify the production of AI models, leveraging symmetry to save time and effort. They guarantee effective computing by modifying code for particular hardware, facilitating quicker testing and deployment. The identification of a suitable and optimal AI framework for development is a multi-criteria decision-making (MCDM) dilemma, where the considered AI frameworks for development are evaluated by considering various criteria and these criteria may have dual aspects (positive and negative). Thus, in this manuscript, we diagnosed a technique of MCDM within the bipolar fuzzy set (BFS) for identification and selection of optimal AI framework for development. In this regard, we diagnosed probability aggregation operators (AOs) within BFS, such as probability bipolar fuzzy weighted averaging (P-BFWA), probability bipolar fuzzy ordered weighted averaging (P-BFOWA), immediate probability bipolar fuzzy ordered weighted averaging (IP-BFOWA), probability bipolar fuzzy weighted geometric (P-BFWG), probability bipolar fuzzy ordered weighted geometric (P-BFOWH), and immediate probability bipolar fuzzy ordered weighted geometric (IP-BFOWG) operators. The diagnosed technique would be based on these invented probably AOs. Afterward, in this manuscript, we took a case study and obtained the optimal AI framework for development by employing the diagnosed technique of MCDM. We also investigated the comparison of the devised theory with certain prevailing theories to reveal the dominance and significance of the devised theory.

Selection of a Forklift for a Cargo Company with Fuzzy BWM and Fuzzy MCRAT Methods

Material handling is a cost-intensive operation for businesses. There are several alternative types of equipment for material handling, therefore it is important to select the best one among them to decrease the cost. As there are several different alternatives and criteria which are used to assess these alternatives, multi-criteria decision making (MCDM) techniques are useful to determine the optimal material handling equipment (MHE) for businesses. In this study, fuzzy BWM for determining weights of criteria and the fuzzy Multiple Criteria Ranking by Alternative Trace (MCRAT) method have been used for ranking forklift alternatives. This study’s significance in the literature will be the creation of a novel fuzzy MCDM technique with the application of fuzzy MCRAT. Furthermore, there are relatively few studies employing the MCRAT approach in the literature; therefore, this study will provide additional data and outcomes from this method to the literature. The findings present that the forklift with the code FLT-3 performed the best, whereas the forklift with the code FLT-2 had the worst performance, according to the fuzzy MCRAT technique. According to the comparison analysis, the fuzzy MCRAT produced the same results as the fuzzy ARAS and had a few subtle differences to fuzzy MARCOS.

Prediagnosis of Disease Based on Symptoms by Generalized Dual Hesitant Hexagonal Fuzzy Multi-Criteria Decision-Making Techniques

Multi-criteria decision-making (MCDM) is now frequently utilized to solve difficulties in everyday life. It is challenging to rank possibilities from a set of options since this process depends on so many conflicting criteria. The current study focuses on recognizing symptoms of illness and then using an MCDM diagnosis to determine the potential disease. The following symptoms are considered in this study: fever, body aches, fatigue, chills, shortness of breath (SOB), nausea, vomiting, and diarrhea. This study shows how the generalised dual hesitant hexagonal fuzzy number (GDHHχFN) is used to diagnose disease. We also introduce a new de-fuzzification method for GDHHχFN. To diagnose a given condition, GDHHχFN coupled with MCDM tools, such as the fuzzy criteria importance through inter-criteria correlation (FCRITIC) method, is used for finding the weight of criteria. Furthermore, the fuzzy weighted aggregated sum product assessment (FWASPAS) method and a fuzzy combined compromise solution (FCoCoSo) are used to rank the alternatives. The alternative diseases are chosen to be malaria, influenza, typhoid, dengue, monkeypox, ebola, and pneumonia. A sensitivity analysis is carried out on three patients affected by different diseases to assess the validity and reliability of our methodologies.

A risk allocation model among the elements of freeway projects in public-private partnership (PPP) method using integrated fuzzy multi-criteria decision-making techniques

ABSTRACT In the present study, an appropriate risk assessment and allocation model was developed between the various elements of PPP based infrastructure projects. For this purpose, after a review of the research literature and identification of the most important risks, with a case study on PPP-based freeway projects in Iran, a systematic model for risk assessment using fuzzy MCDM methods including FAHP has developed in order to critical risk assessment (Objective 1), FTOPSIS Identification of Common Risks in PPP Transportation Projects (Objective 2) and FDEMATEL for Allocation and Impact of Risk Between Different Project Elements (Objective 3). The results of risk analysis by FAHP method showed that economic and financing, construction and operational risks have the greatest impact, respectively. In addition, the results of FTOPSIS method showed that projects Isfahan-Shiraz Freeway, Salafchegan-Arak Freeway and Khorramabad-Arak Freeway, respectively, were more affected by risks. Finally, the results of FDEMATEL analysis show the degree of interaction and impact strength of risks for each risk and from the perspective of each project manager, which indicates a significant relationship between different risks. The results of this research can be used as a management model in the process of evaluation and risk management of PPP projects.

Multi-attribute sustainability assessment of wastewater treatment technologies using combined fuzzy multi-criteria decision-making techniques

Water, which is predicted to be one of the most critical resources for the near future, also plays a vital role in society's sustainable development. Wastewater treatment is a critical part of the circular water management system and offers various technological alternatives. Taking appropriate decision for the technology selection is, therefore, essential for a long-term perspective. A complex yet imperative process is the sustainable selection of the wastewater treatment process. This paper presents the use of multi-criteria decision-making (MCDM) in the sustainability assessment of wastewater treatment technologies that may be very relevant to the growing sector with many emerging options. A comparison of six wastewater treatment technologies based on four sustainability parameters using three MCDM techniques, namely FSWARA, FMOORA and FTOPSIS is presented in detail. FSWARA is used for weighting criteria and the other two for technology ranking. The detailed step-by-step comparison study is presented and the results were somewhat predictable for the study, and this confirms the reliability of the methodology. This paper's primary objective is to propose a well-defined increscent practice for making sustainable wastewater treatment decisions among state-of-the-art technologies.

Investigating the Indicators and Components of the Institutional Resilience Approach in Urban Incident Management in Iran

INTRODUCTION: Paying attention to different dimensions of resilience is one of the main goals of sustainable development, especially in cities and urban communities with potential risks, and institutional resilience as one of the dimensions of resilience is an important approach to strengthening communities and cities. METHODS: This applied research was conducted based on a descriptive-analytical design. The VIKOR method which is a fuzzy multi-criteria decision-making technique was used for analysis. Library and documentary methods were used to collect data and the data collection tool was a seven-7-item questionnaire. FINDINGS: Based on the findings, the organizational structure and the experience of previous incidents held the first and last places. preparedness policies, manager’s effectiveness in prevention, the effectiveness of training, incidence experiences in resource needs assessment, and the impact of financial resources ranked the first in the following sections: organizational structure, education, leadership, the experience of previous disasters, and capacity, respectively. CONCLUSION: As evidenced by the results of this study, each of the indicators found in this study had an important role to play in the management of urban incidents in the country. Therefore, their management is of paramount importance in the achievement of sustainable urban development in the country.

Combining life cycle sustainability assessment and fuzzy multicriteria decision making method for prioritizing the flare technologies in the oil, gas, and chemical plants

AbstractLife cycle sustainability assessment (LCSA) of flare technologies can assist the stakeholders/decision‐makers to choose the most sustainable flare technology in life cycle outlook among multiple options. This article purposes in developing a framework of life cycle sustainability decision‐support for prioritizing the flare technologies by integrating the LCSA concepts and fuzzy multicriteria decision making (MCDM) method. A novel fuzzy MCDM (FMCDM) technique that can handle linguistic variables in the decision‐making matrix was progressed by integrating SWARA–WASPAS approach and fuzzy evaluation (fuzzy SWARA–fuzzy WASPAS). Using fuzzy SWARA is obtained the weights of the metrics for LCSA and then, fuzzy WASPAS is employed to prioritize the alternatives with considering the metrics. Finally, the findings of fuzzy SWARA show the “Production cost,” having the topmost weight with value of 0.5094, is the foremost metric that overshadows the choice of suitable and sustainable flare technology. The results obtained from the fuzzy WASPAS suggest that “Steam‐assisted flare,” is the highest prioritized and thus, the most significant alternative to employ flare technology in oil, gas, and chemical plants. The results indicate that combining LCSA and MCDM can effectively rank industrial systems and equipment under data uncertainties.

A Decision Framework for Solar PV Panels Supply Chain in Context of Sustainable Supplier Selection and Order Allocation

Sustainable supplier selection and order allocation (SSSOA) is paramount to sustainable supply chain management. It is a complex multi-dimensional decision-making process augmented with the triple bottom line of sustainability. This research presents a multi-phase decision framework to address a SSSOA problem for the multi-echelon renewable energy equipment (Solar PV Panels) supply chain. The framework comprises of fuzzy Multi-Criteria Decision-Making techniques augmented with fuzzy multi-objective mixed-integer non-linear programming mathematical model. The various economic, environmental, and social objectives were optimized for a multi-period, multi-modal transportation network of the supply chain. The results show that among the various sustainable criteria selected in this study, product cost, environmental management system, and health and safety rights of employees are the most important for decision-makers. The results of the mathematical model highlighted the impact of multimodal transportation on overall cost, time, and environmental impact for all periods. An analysis of results revealed that transfer cost and customer clearance cost contribute significantly towards overall cost. Furthermore, defect rate was also observed to play a critical role in supplier selection and order allocation.

A novel hybrid evaluation framework for public organizations based on employees’ performance factors

Performance evaluation is a comprehensive process for comparing activities compared with predetermined organizational criteria. Based on the results of performance evaluation, organizations can embark on purposeful actions to improve their situation. Obviously, the success of organizations and the economic development of the country depend on the performance of human resources (HR). This paper proposes a novel hybrid evaluation framework for analyzing the performance of public sector organizations. The suggested setting allows for performance evaluation based on a comprehensive approach involving expert knowledge. For this purpose, the research integrates the Balanced Scorecard (BSC) approach and fuzzy multi-criteria decision-making (MCDM) methods. Initially, the employees’ performance factors (criteria) are identified from the literature based on the BSC dimensions. Then, the most relevant of them are finalized through the fuzzy Delphi method (FDM) questionnaires and experts’ opinions. In the second stage, the weights of criteria are determined by adopting the fuzzy best-worst method (FBWM). Moreover, two fuzzy MCDM techniques, namely VIKOR and Grey Relational Analysis (GRA), are used to examine the performance of the eight important public sector organizations of Iran. Finally, a Monte Carlo simulation-based (MCSB) approach and a scenario-based (SCB) approach are applied to compare the effectiveness of fuzzy VIKOR and fuzzy GRA. The results suggest that the critical employees’ performance factors include sharing knowledge with colleagues (0.136), optimal use of facilities (0.123) and participation in solving organizational issues (0.118). Additionally, based on the implemented sensitivity analysis approaches, fuzzy VIKOR generates more reliable results and also has higher robustness than fuzzy GRA.

Prioritization of laminate flooring selection criteria from experts’ perspectives: a spherical fuzzy AHP-based model

ABSTRACT Laminate flooring selection is an important phase in the design and construction of a building. Owing to the subjectivity and conflicting factors, the fuzzy multicriteria decision-making technique can be used for handling the problem. In this study, it is aimed to prioritize laminate flooring selection criteria from experts’ perspectives. Five main criteria and twenty subcriteria are determined with the help of experts. A three-level hierarchy is devised for comparisons. The spherical fuzzy analytic hierarchy process is used to determine the importance of each criterion. According to the results, ‘safety and health properties’ (29.0%) and ‘durability properties’ (20.6%) are the most significant main criteria. Furthermore, ‘walking safety’ (10.7%), ‘free of harmful substances’ (8.6%), and ‘scratch resistance’ (6.7%) are found as the most important subcriteria. The proposed approach presents a different view because it contributes to analyzing the key attributes of laminate flooring. The findings of this study will help building owners, architects, and designers in making informed choices.

Evaluation of energy alternatives for sustainable development of energy sector in India: An integrated Shannon’s entropy fuzzy multi-criteria decision approach

In this paper, conventional and renewable energy sources for sustainable development of energy sector in India are evaluated from multiple perspectives including economic, technical, social, environmental, political, and flexible criteria. An integrated Shannon’s entropy multi-criteria decision making (MCDM) method has been used for the evaluation and assessment of these sources. Thermal, gas, nuclear, solar, wind, biomass, and hydro energy options are used as the alternatives in the decision model. Shannon’s entropy method is applied to determine the weights of decision criteria, and fuzzy analytical hierarchy process (AHP) method is applied to prioritize sustainable energy alternatives. The output of the proposed model was compared with six different fuzzy MCDM techniques for the establishment of correlation index. Solar energy was shown to be particularly well suited for India followed by wind and hydro energy sources. Later, the study has developed fourteen scenarios, considering the first five sustainable energy sources (solar, wind, hydro, biomass, and gas power), to evaluate the optimal energy mix scenario for the sustainable development of energy sector in India. An optimal energy mix scenario carries the heroic development of solar, wind, and hydro energy with cross border import-export facility for the time frame of the year 2030.

Determining the Optimal Method of Allocating Credits and Granting Facilities in the Student Welfare Fund of Ministry of Health and Medical Education using Fuzzy AHP

Introduction: Student support systems try to provide access to higher education for students from all socio-economic backgrounds, which is itself one of the main pillars of sustainable development. This study aims to identify the types of material and spiritual support of students in the world and to study the support institutions of students in the country while devising practical indicators for granting facilities to students and prioritizing these types of indicators using fuzzy analytical hierarchy process (FAHP) method to choose a model to provide this type of support as efficiently and effectively as possible and be able to establish justice in this type of support. Research Method: The present study is descriptive-analytical in terms of purpose, practical in terms of results, library and survey research in terms of data collection method with a cross-sectional time horizon that includes qualitative and quantitative phases. First, by studying 18 developed countries due to access to information on official websites and relevant valid articles and booklets, as well as studying student support organizations in the country, basic information and complete knowledge of the issues of different groups of students and methods of addressing or meeting these needs were acquired. Then, in a working group discussion consisting of student facilities experts of the Student Welfare Fund, the extracted indicators were divided into two categories with the pillars of need (with 10 sub-criteria) and competence (with 7 sub-criteria) each in two subgroups according to the nature of each indicator. Then, using fuzzy multi-criteria decision-making techniques, a decision-making hierarchy was created. The criteria in pairs in the form of a pairwise-comparison-survey were asked from 10 expert decision-makers in the fund. Finally, each criterion was weighted itself. Findings: The results showed that in the countries studied, various criteria are considered according to the support policies of countries in granting the desired student facilities, but in a general and comprehensive view, these criteria can be categorized into two groups of need and competence. In Iran, according to the criteria devised in the Student Welfare Fund, the indicators of need are preferable in general comparisons with the indicators of competence, and in the sub-criteria of need in the order of special events that are subjected to the students. The student’s health condition, the presence of dependents of students, were three indicators of importance. Conclusion: Given the living condition of students and the importance of this segment of society in the sustainable development of the country, traditional methods of credit allocation based on the previous years do not have the necessary effectiveness and efficiency to provide scientific growth and increase in the level of student welfare that results in the scientific growth and development of the country. Therefore, the fuzzy multi-criteria decision-making method and the use of the indicators of need and competence devised in the research provides great coordination and flexibility in student-oriented credit allocation in terms of management and leads to improved justice in granting facilities.

Prioritization of Renewable Energy Alternatives for China by Using a Hybrid FMCDM Methodology with Uncertain Information

With the deteriorating ecological environment and increasing energy consumption, developing clean and renewable energy sources has become a key measure to solve environmental problems and energy shortages. The multicriteria decision-making (MCDM) technique is widely used in the assessment of renewable energy alternatives (REA) to determine the most sustainable and appropriate option for a country or region. Classic REA ranking is conducted in a deterministic environment through MCDM techniques. However, with the increasing complexity of environmental and energy issues, the REA ranking method is unsuitable for use in today’s China. Therefore, in this paper, a fuzzy MCDM technique based on the interval-valued hesitant fuzzy elimination and choice expressing reality (IVHF-ELECTRE II) method, taking into account the uncertainty and ambiguity of the information, is proposed for REA ranking. A case study in China is conducted to elaborate on the rationality and feasibility of the proposed framework. According to the ranking results, hydro is determined as the best REA in China, followed by wind energy, solar photovoltaic, geothermal, biomass energy, and solar thermal. This research provides a feasible method and insightful reference for national decision-makers to utilize when evaluating the REA and establishing a macroplanning policy for renewable energy under an uncertain environment.

Sustainable supplier selection under attractive criteria through FIS and integrated fuzzy MCDM techniques

ABSTRACT Suppliers as upstream partners play a crucial role to establish sustainability in the supply chain. For precise evaluation of the supplier’s performance on sustainability criteria researchers have mainly focused on Multi-Criteria Decision Making (MCDM) and Fuzzy Inference System (FIS) approaches. The objective of the paper is to evaluate the supplier’s sustainability performance through FIS and fuzzy MCDM approaches. Further, the results are compared and utilised to develop the Sustainable Supplier Selection (SSS) framework for the iron and steel industry of India. To calculate Suppliers Performance Index (SPI), three distinct FIS engines have been developed for each sustainability dimensions and fuzzy AHP and TOPSIS techniques are used for the MCDM environment. The results provide a deep inside of the sustainability performance of each supplier. It elicits from the results of two approaches, that ranks are interchanged among the top two suppliers.

Assessment of the performance of nurses based on the 360-degree model and fuzzy multi-criteria decision-making method (FMCDM) and selecting qualified nurses

BackgroundHuman resources is the most prominent asset of an organization. Despite the constant effort to design optimal and effective systems for assessing employees, evidence shows that managers are not satisfied with the methods and systems to assess employees. ObjectivesResearchers wanted to assess the performance of nurses based on the 360-degree model and fuzzy multi-criteria decision-making technique (FMCDM) and selecting qualified nurses. MethodsThe present study is descriptive and conducted in 2016 in a hospital at Kashan University of Medical Sciences. This study conducted in three ‏stages. 1) Identification of criteria and sub-criteria for the performance assessment that classified into five groups (technical skills, human skills, and perceived skills; individual characteristics; and compliance with the organization's rules and regulations). 2) Weighing the criteria and sub-criteria based on the DEMATEL-ANP (DANP) method in a fuzzy environment. 3) Assessing the performance of nurses based on the 360-degree model, which includes supervisors, coworkers, self-assessment, and patients and their companions. In this stage, four groups used the VIKOR questionnaire to assess the performance. ResultsAmong five criteria of assessment, “Human Skills” earned a top score, and among 21 sub-criteria, “Identify the strengths and weaknesses,” “Suitable relationships with patients,” and “Partnership with colleagues” earned the top score. In the 360-degree model, the supervisor's assessment score was 0.521, with the highest weight, and the self-assessment was 0.042 with the lowest weight. Finally, nurse 3 in children and infants ward earned the highest ranking. ConclusionsThe advantage of the proposed method is more realistic results than other methods because the criteria and sub-criteria are weighted, and the importance of each is determined. Hospitals can use the results of this study to assess the performance of medical groups.

Investigating the satisfaction of citizens in municipality services using fuzzy modelling

Rapid developments in communication and information technologies in the world force local administrators to be more effective. For a local administrator to be elected again, satisfaction of citizens with the duties that need to be performed and the services provided is significant. In this study, citizen satisfaction with municipality services was measured using a questionnaire on a household level. It was aimed to develop a new approach in evaluation of municipal service quality.The data that were obtained were analyzed with fuzzy multi-criteria decision-making techniques. For determination of criterion weights, FDEMATEL was utilized, and for household-based ranking, the FTOPSIS technique was implemented. A raster map was created in the ArcGIS geostatistics module by applying IDW interpolation on the resulting values. The map that was produced visually revealed the satisfaction of citizens regarding the quality of municipality services based on location. When the map was analyzed, it was seen that the satisfaction levels in the study areas of two neighborhoods were high, while the levels in the study area of one neighborhood was low.

Multi-criteria decision making under uncertainty via the operations of generalized intuitionistic fuzzy numbers

Multi-criteria decision making (MCDM) is the most important approach to apply and solve many complex real-world decision-making problems where choice among alternatives is concerned. However, classical MCDM approaches are inappropriate to take decision when parameters are uncertain, imprecise or vague in nature. In such situations, fuzzy set theory comes into picture and accordingly fuzzy multi-criteria decision making (FMCDM) has been introduced to deal with such problems. Later, MCDMs have been performed using intuitionistic fuzzy set. It is encountered that FMCDM techniques are performed using arithmetic of generalized intuitionistic fuzzy numbers (GIFNs) which produce counterintuitive output more often. That is, it is found that evaluation of arithmetic operation of GIFNs is always a crucial issue. In this paper, an attempt has been made to perform FMCDM using generalized triangular Intuitionistic fuzzy numbers (GTIFNs) by devising a novel technique of arithmetic operations between GTIFNs. The major contribution of the present approach is that the arithmetic of GTIFNs produces generalized trapezoidal intuitionistic fuzzy numbers and this approach has the ability to effectively resolve the drawbacks of the conventional arithmetic operations between GTIFNs. Furthermore, it gives rational results and outperforms in all the situations.

A predictive filtering approach for clarifying bibliometric datasets: an example on the research articles related to industry 4.0

ABSTRACTThis study proposes a filtering approach based on text classification and a fuzzy multi-criteria decision-making technique to select the relevant bibliometric data for further analyses in the scope of bibliometrics, scientometrics, and related methodologies. The proposed approach is illustrated on Industry 4.0 and internet of things which are the concepts that currently draw utmost attention with a growing number of research and applications. Accordingly, various findings are presented revealing the characteristics of the selected bibliometric data with the help of text and network analytics. The potential contribution of this study is two-fold such that the study not only suggests a novel approach for clarifying the retrieved bibliometric data but also emphasises the mainstream research areas and directions of Industry 4.0 along with the concept of the internet of things. Thus, an analysis framework with computing techniques has been used to reveal the characteristics of literature in a field of technology.

Evaluating food supply chain performance using hybrid fuzzy MCDM technique

A Performance Measurement System of any Food Supply Chain (FSC) consists of a complex array of performance criteria and their indicators which seems interdependent. There is a need to evaluate the performance of FSC with the help of important criteria and associated key indicators. In this study, we have identified the six important performance criteria and their key indicators using the integrated approach of literature review & expert opinions.Further, we have employed the approach of fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) to corroborate the interrelationships among the identified performance criteria and their associated indicators. Study undertakes prioritisation of performance measures or criteria of FSC with the help of an upcoming concept of hybrid Multi-Criteria Decision Making (MCDM) technique. The study further utilises the performance indicators of FSC which are comprehensive and reflects the significant characteristics. Results identify three highly essential performance criteria (i.e., ”service to the customer” ”quality” and ”supply chain efficiency”) with top five important key indicators as ”customer satisfaction”, ”customer complaint”, ”on time delivery”, ”reverse logistics” and ”process quality”. Finding suggests towards proper coordination & collaboration among the partners within the framework of an FSC. The study considers, “Information sharing” as an essential factor for improving the coordination and collaboration in the supply chain. A significant limitation of this research is the subjective inputs of experts who belong to demography.