Fuzzy Group Decision Research Articles

Multi-attribute approach for selection of polymeric materials for manufacturing gears: A case study in the automotive industry

Automotive industry is characterized by mass production, a large share in the gross national income and high employment of workers with different knowledge and skills. Improving the production process, as well as product quality, is one of the most important tasks of automotive enterprise as well as government management. This research promotes a new fuzzy hybrid model for determining the priority of polymeric materials for manufacturing gears in an exact manner, which leads to an incremental improvement in the quality of the considered product. The analysis of polymeric materials and their characteristic is based on data from the relevant literature and experiences of the best practice. The relative importance of material characteristics is stated as fuzzy group decision making problem. The weights vector is determined by using the fuzzy Analytic Hierarchical Process and fuzzy geometric mean. The rank of polymeric materials is obtained by employing the proposed Technique for Order Preference by Similarity to Ideal Solution with triangular fuzzy numbers. The fuzzy algebra rules have been used for determining: (i) distances from Fuzzy Positive Ideal Solutions and Fuzzy Negative Ideal Solutions and (ii) closeness coefficient values. The proposed fuzzy hybrid model testing and verification are performed on real data in an automotive enterprise.

Evaluation of Community Regeneration Planning and Resilience Based on Fuzzy Group Decision-Making Method

Evaluation of Community Regeneration Planning and Resilience Based on Fuzzy Group Decision-Making Method

A fuzzy reliability assessment methodology for city gas stations based on an extended T-S fault tree

City gas stations (CGSs) play a crucial role in ensuring a stable and safe supply of natural gas to urban users. However, as the service time of stations increases and the performance of components deteriorates, concerns about the safety and reliability of these station have grown among operators and local government authorities. This paper proposes a fuzzy reliability assessment methodology for CGSs that considers the polymorphism of component faults and the uncertainties associated with fault relationships, failure probabilities, and fault magnitudes. The methodology utilizes T-S fuzzy gates to describe the correlation among events and constructs a T-S fuzzy fault tree for CGSs. Component fault states are represented using fuzzy numbers, and a fuzzy group decision-making approach is introduced to evaluate the current fault magnitude of components. To handle the uncertainty caused by sparse failure sample data, a Bayesian updating estimation method is presented to estimate the failure probabilities of components. Furthermore, T-S fuzzy importance analysis is applied to identify the weak points in the CGS system. The effectiveness of the developed methodology is demonstrated through a case study of reliability analysis of a city gas distribution station. The research findings provide valuable support for optimizing the design and implementing preventive maintenance of CGSs.

Conflict elimination based on opinion dynamics in fuzzy group decision-making

The different preferences of experts in fuzzy group decision-making problems will lead to conflict, which hinders the reaching of consensus. In present conflict management techniques, local conflict among individual experts or the overall level of conflict is often concerned. This paper deals with conflict relations by opinion dynamics to resolve the whole and local conflicts among experts. This paper proposes a conflict resolution method based on opinion dynamics, which mainly includes three parts: (1) trust propagation: taking the consistency index into account in the propagation of trust, aiming at making as objective an assessment as possible of the competence and social status of experts; (2) conflict detection and elimination: reducing conflicts to an acceptable level through multiple rounds of preference adjustment according to the harmony degree; (3) alternatives selection: proposing a scoring function combining extent superiority with number superiority to score and rank the alternatives. Finally, a numerical example is given to illustrate the feasibility of the proposed method.

An approach for fuzzy group decision making and consensus measure with hesitant judgments of experts

An approach for fuzzy group decision making and consensus measure with hesitant judgments of experts

A fuzzy group decision-making model for Water Distribution Network rehabilitation

ABSTRACT Group Decision-Making (GDM), though could aid water companies in determining the Pipeline Rehabilitation Plans (PRPs) in any network size, can impose uncertainties on PRPs due to the different viewpoints of decision-makers. Thus, it should be determined when GDM could be ignored or should be considered for PRPs. To address this problem, a Fuzzy GDM model was developed to assess 10 scenarios of GDM in combination with 7 scenarios of network size. Hence, by participating experienced experts in different countries, PRPs were determined for various network sizes in a case study. The results indicated that the GDM could be ignored for PRPs with fewer pipes, whereas, should be considered for PRPs with more pipes. In addition, it was found that the groups with more decision-makers had less effect on pipes prioritization, but more influence on determining rehabilitation strategies. While, in groups with fewer decision-makers, the GDM could have the reverse effect.

An Analysis of Fuzzy Group Decision Making to Adopt Emerging Technologies for Fashion Supply Chain Risk Management

An Analysis of Fuzzy Group Decision Making to Adopt Emerging Technologies for Fashion Supply Chain Risk Management

An Improved Similarity-based Fuzzy Group Decision Making Model through Preference Transformation and K-Means Clustering Algorithm

Group decision making plays a crucial role in organizational and community contexts, facilitating the exchange of expert opinions to arrive at effective decisions. The concept of preference, reflecting an individual's subjective evaluation of criteria or alternatives, forms a foundational element in this process. This study focuses on transforming non-fuzzy preferences, such as preference ordering and utility functions, into fuzzy preference relations (FPR) to address the uncertainty and uniformity inherent in expert preferences. To further enhance decision-making, we assess and visualize the similarity among the experts' uniform preferences. Integrating the K-means clustering algorithm into the fuzzy group decision making model allows for the predetermination of an appropriate number of groups based on the available alternatives. By aggregating individual preferences, we present a final ranking of alternatives. The enhanced methodology, as demonstrated through comparative analysis, showcases its ability to yield positive benefits when applied to decision-making applications.

Fermatean Fuzzy Group Decision-Making Based CODAS Approach for Taxation of Public Transit Investments

The provision of public goods is always a controversial issue in many aspects. Even some additional financial resources can provide public transit systems, the tax revenues constitute a significant part of the investments in practice. Yet, governments should make an important decision regarding tax schemes. This article focuses on how to identify the best tax scheme to finance public transit investments. A three-phase Fermatean fuzzy group decision-making approach is developed to solve the highlighted problem. Qualifications and experience of experts are considered to distinct their reputations. A Fermatean fuzzy direct rating method is introduced to evaluate criteria importance. A Fermatean fuzzy combinative distance-based assessment method is formulated to assess tax schemes. The study provides valuable policy implications and decision-making guidelines using a real-life case. The results show that beneficiaries of public services should pay more, and tax collectors are encouraged to use progressive tax schemes instead of the equal distribution of the cost to the taxpayers. The sensitivity analysis to changes in the threshold parameter is given. The comparative analysis with all state-of-the-art Fermatean fuzzy set based multicriteria decision-making methods is provided. The Fermatean fuzzy group decision-making approach is highly robust and reliable. The approach can solve other public transportation problems.

Sustainability Assessment of Regional Transportation: An Innovative Fuzzy Group Decision-Making Model

In this paper, an innovative fuzzy group decision-making model is designed for assessing regional transportation sustainability, focusing on the correlation between various attributes of the evaluation system. The focus of this model is the partitioned Maclaurin symmetric mean operator because of its better applicability when considering attribute correlation and attribute grouping. The modified spherical fuzzy partitioned Maclaurin symmetric mean operator is proposed, which has superior application scope. Its weighted form and special cases are discussed. Then, the extended statistical variance method and the evidence-based Bayes approximation method are used to obtain weight vectors of attributes and experts. In addition, a fuzzy assessment model of sustainable transportation is developed. Finally, a numerical example of regional transportation sustainability assessment and a comparison with previous studies are presented to illustrate the feasibility and universality of this method.

Addressing last-mile delivery challenges by using euclidean distance-based aggregation within spherical Fuzzy group decision-making

Optimal location selection plays a crucial role in enhancing logistic performance and addressing inefficiencies in last-mile delivery. Parcel lockers have emerged as an efficient solution in this regard. In the context of optimizing last-mile logistics in Dublin, Ireland, this research strives to identify the ideal locations for parcel lockers. It does so by pioneering the application of a unique decision-making model. To navigate the inherent uncertainties in decision-makers' preferences, the study harnesses the power of the Analytic Hierarchy Process (AHP) in Spherical Fuzzy environment with the Euclidean Distance-Based Aggregation Method (EDBAM) for the selection of parcel locker locations. The harmonious integration of these methodologies serves to mitigate the deterministic shortcomings typically associated with the AHP approach, presenting an innovative and robust solution for enhancing last-mile delivery efficiency. The outcomes of this research will provide valuable insights to policymakers in making informed strategic decisions regarding the selection of parcel locker locations in Dublin City.

A new compatibility model for fuzzy group decision making by using trapezoidal fuzzy preference relations with COWA operator

A new compatibility model for fuzzy group decision making by using trapezoidal fuzzy preference relations with COWA operator

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.

Scenario analysis for renewable energy investment using a hybrid framework: A case study in Saudi Arabia

This study aims to analyse potential future renewable energy investment scenarios and the evaluation criteria that influence the selection of an optimal scenario. For the first time in studying the renewable energy sector, a hybrid framework is proposed to address the selection process. The proposed hybrid framework combines these multi-disciplinary approaches: considering macroeconomic assumptions, using historical information as quantitative data and eliciting judgements from decision experts as qualitative data. Moreover, it tackles uncertainty regarding the future direction of renewable energy investments by utilising Intuitionistic Fuzzy Set theory. An application of the proposed hybrid framework for a case in Saudi Arabia was conducted in three phases. The first phase applied Leontief’s input-output model and proposed three investment scenarios by 2030, namely: the ‘based scenario‘ (investment of 112 billion Saudi Riyals), an ‘alternative scenario 1’ (investment of 75 billion Saudi Riyals) and an ‘alternative scenario 2’ (investment of 25 billion Saudi Riyals). The second phase established five decision criteria that are considered when selecting an optimal investment scenario, namely: ‘Economic’, ‘Environmental’, ‘Social’, ‘Public preferences’ and ‘Risk’. The third phase applied a Fuzzy Group Decision Support model to rank the scenarios. The results indicate that the ‘based scenario‘ and the ‘alternative scenario 1’ are always the compromise investment scenarios and that ‘alternative scenario 2’ is not preferred. A sensitivity analysis was applied to validate the results.

A Fuzzy Group Decision-making Model for Measurement of Companies' Performance

A Fuzzy Group Decision-making Model for Measurement of Companies' Performance

МЕТОДЫ НЕЧЕТКОГО МНОГОКРИТЕРИАЛЬНОГО ГРУППОВОГО ПРИНЯТИЯ РЕШЕНИЙ ДЛЯ ЗАДАЧ ЭВАКУАЦИИ ПРИ ЧРЕЗВЫЧАЙНЫХ СИТУАЦИЯХ

The purpose of this article is to analyze the current state of research in the field of fuzzymulticriteria optimization methods, as well as the development of aggregation operators and algorithmsusing fuzzy multicriteria group decision-making using an intuitionistic attitude of linguisticpreferences. The most well-known fuzzy methods of multicriteria optimization are presented:ELECTRE, PROMETHEE, VIKOR, TOPSIS, AHP, ANP, MACBETH, DEMATEL, Shoke integraland DEA, their features, applications and the most cited articles are considered. Most real optimizationproblems may have conflicting goals. The method of fuzzy multi-purpose decision-makingFMODM is also presented for situations where there are inaccuracies and uncertainty in somegoals and variables on which they depend; methods of fuzzy multi-purpose linear programmingFMOLP, fuzzy multi-objective target programming FMOGP and fuzzy heuristic decision-makingmethods. The problem of fuzzy multicriteria group decision-making during evacuation with anintuitive relation of linguistic preferences is considered. It is noted that fuzzy logic methods areparticularly suitable for making evacuation decisions when there is little data, knowledge ofcause-and-effect relationships is inaccurate, and observations and criteria can be expressed inlinguistic qualitative terms. The main stages of group making the best decision among alternativesin a fuzzy environment are presented: combining expert assessments; obtaining a final assessmentfor each alternative represented by a linguistic variable; ranking alternatives; group making themost preferred decision. An approach to group decision-making with an intuitive preference relationshipbased on aggregation procedures is proposed. The group model of decision-making andthe concept of fuzzy group decision and linguistic variables used in predicting an emergency situationand planning evacuation are considered. It is noted that the well-known operators of orderedweighted averaging OWA, LOWA do not take into account the weights of experts. The Low operatoris defined, which allows taking into account the weight values of experts, as well as an approachto determining a fuzzy group solution of aFCS as a type 2 set. Algorithms for determininga fuzzy group multicriteria solution based on aFCS are presented

Prioritization of strategies for a sustainable regional transportation infrastructure by hybrid spherical fuzzy group decision-making approach

Prioritization of strategies for a sustainable regional transportation infrastructure by hybrid spherical fuzzy group decision-making approach

Material selection of sustainable composites by recycling of waste plastics and agro-industrial waste for structural applications: A fuzzy group decision-making approach

Recycling of waste plastics (WP) for the development of sustainable composite materials is one of the effective methods to deal with the problems of the generated plastics wastes. The research proposes an integrated Analytical Hierarchy Process-Techniques for Order Preference by Similarity to Ideal Solution (AHP-TOPSIS) approach based on triangular fuzzy weighted Bonferroni mean operator (TFWBMO) for the selection of an appropriate composition for development of floor tiles by recycling WP and agro-industrial wastes. The decision hierarchy has been formed by collecting the experts' opinion from five different academicians and personalities engaged in the domain of sustainable composites. The present work suggests that the amalgamation of 90 wt % of low-density polyethylene with 10 wt % of fillers is a suitable composition for structural applications. The comparative analyses of the results with well-known techniques and sensitivity analyses have confirmed the reliability of the proposed model. Moreover, Spearman's rank correlation coefficient (SRCC) has verified the statistical consistency of the proposed model. The proposed mathematical model is efficient in handling the vagueness in decision-making and hence can be successfully implemented to overcome the issues of material selection in large scale production of sustainable structural materials. The research has explored the potential of WP in the replacements of the conventional structural materials by a sustainable composites possessing expedient features.

A novel fuzzy group decision-making approach based on CCSD method for thermal insulation board selection problem: A case study

Due to buildings’ high energy consumption and environmental impacts, selecting an appropriate thermal insulation board is crucial in reducing energy consumption in an existing building. Therefore, thermal insulation board selection has become an important issue. This study presents a combined fuzzy group decision-making approach that consists of the integrated fuzzy analytic hierarchy process and fuzzy technique for order preference by similarity to ideal solution, the integrated intuitionistic fuzzy analytic hierarchy process and intuitionistic fuzzy technique for order preference by similarity to ideal solution, and intuitionistic fuzzy technique for order preference by similarity to ideal solution for effectively evaluating thermal insulation boards. However, since these three fuzzy decision-making methods can produce different rankings, decision-making is a complex and challenging process for decision-makers. In order to overcome this problem, correlation coefficient and standard deviation method is utilized to construct the final ranking by integrating these approaches using regression statistics, standard deviations, and correlation coefficients between the closeness coefficients of each alternative in the relevant approach. The proposed approach provides an accurate ranking of thermal insulation boards validated through a real-world case study. Furthermore, the sensitivity analysis indicates that the combinations of different levels of criteria and approaches affect the final ranking. According to the study’s findings, the gray expanded polystyrene foam is the most suitable thermal insulation board in the combined fuzzy group decision-making approach.

Nonconformity Assessment in Building Construction Projects: A Fuzzy Group Decision-Making Approach

Construction nonconformity assessment of buildings is critical to ensure the anticipated quality and living safety for their future occupants. Previous studies have paid less attention to identifying and analyzing building construction nonconformities (BCNs) in the design and construction (D&C) phases. They considered expert judgments in nonconformity assessment, which are critiqued for human bias, uncertainty, and imprecision. In a BCN assessment, previous studies also did not consider the specific time frame to detect construction nonconformities. This study aims to prioritize nonconformities in the D&C phases, addressing the limitations of expert judgment by applying the fuzzy group decision-making approach (FGDMA). The FGDMA computes the defuzzified scores of the nonconformities to prioritize and identify critical nonconformities. The defuzzified scores are explained further by associating them with the corresponding fuzzy numbers to address the limitations involved in expert judgments. The study also identifies the detection time of BCNs and analyzes 15 different Bangladeshi project scenarios to understand their context better. The critical nonconformities identified include premature stressing on concrete, inaccurate water-cement ratios, insufficient concrete compaction, lack of full-time site supervision, and the absence of stirrups in beam-column joints. Critical nonconformities are mostly identified during construction, and residential, commercial, and multipurpose buildings, regardless of ownership (i.e., public or private) and size, have experienced poor quality construction. This study will assist major stakeholders (owner, contractor, consultant, and regulatory authorities) to fully understand the critical nonconformities in different building projects from their preconstruction to construction phases for better quality assurance in providing a safe living and working environment for their future occupants.