Fuzzy Assessment Research Articles

Safe E-scooter operation alternative prioritization using a q-rung orthopair Fuzzy Einstein based WASPAS approach

E-scooters globally have proven an increasingly popular form of dockless micro-mobility, while also contributing to sustainable urban transportation forms. However, some safety issues arise with e-scooter use in the cities. This study aims to propose a decision-making model based on q-rung orthopair fuzzy sets for prioritizing the safe e-scooter operation alternative. The proposed model consists of two stages: weighting the criteria and ranking the alternatives. First, a fuzzy logarithmic additive assessment of the weight coefficients methodology and fuzzy Einstein weighted averaging operator were applied to define the reference relationships between the criteria and determine their weights. Second, a q-rung orthopair fuzzy sets based decision-making model integrating q-rung orthopair fuzzy Einstein average and q-rung orthopair fuzzy Hamacher geometric mean operator was used to rank the alternatives. A fictional case study is presented to show the practicality of the proposed model. The contribution of the work is as a decision-support system for evaluating safe e-scooter strategies, including infrastructure placement, user behavior and how e-scooters interact with other transportation means, showing that applicability of the proposed model to real-world problems.

Improved urban flood risk assessment based on spontaneous-triggered risk assessment conceptual model considering road environment

Urban flood risk assessment is an important tool for urban disaster management. The current research mainly considered area itself as the evaluation object. Urban road networks are extremely vulnerable to floods as a basis for all socio-economic activities in the city. However, most studies on road environmental risk assessment only took road itself as the evaluation object and did not consider potential regional system risks such as traffic jam caused by road inundation. Based on this, this study proposes a spontaneous-triggered risk assessment (STRA) conceptual model that comprehensively considers the spontaneous risk (SR) caused by the subregional hazard, socio-economic exposure, and triggered risk (TR) from the cross-subregional traffic jam or interruption caused by the road inundation in the evaluated subregion. Taking Haidian Island in Haikou as an example, six indices were selected for the SR assessment based on the combined weight-gray fuzzy comprehensive risk assessment method. The maximum mean inundation depth of road (RMD), maximum inundation duration of road (RID), road betweenness centrality (RBC), and number of road bus lines (RBL) were selected for the TR assessment. Total flood risk (FR) of the study area was obtained by combining the two. The results indicate that, compared with the traditional SR, the highest and higher risk subregions are more concentrated in the study area center, and the risk of the outer ring subregions is reduced overall after considering the TR. According to statistics, the FR level of 68 subregions is lower than the SR level, most of which are in the outer ring of the study area, and the FR level of 17 subregions is higher than the SR level, most of which are located around the intersection of Haidian Fifth Road and People Road. The study outcomes provide a novel approach for flood risk assessment.

An extended WASPAS approach for teaching quality evaluation based on pythagorean fuzzy reducible weighted Maclaurin symmetric mean

Teaching quality evaluation (TQE) can not only improve teachers’ teaching skills, but also provide an important reference for school teaching management departments to formulate teaching reform measures and strengthen teaching management. TQE is a process of grading and ranking a given teachers based on the comprehensive consideration of multiple evaluation criteria by expert. The Maclaurin symmetric mean (MSM), as a powerful aggregation function, can capture the correlation among multiple input data more efficient. Although multitude weighted MSM operators have been developed to handle the Pythagorean fuzzy decision issues, these above operators do not possess the idempotency and reducibility during the procedure of information fusion. To conquer these defects, we present the Pythagorean fuzzy reducible weighted MSM (PFRWMSM) operator and Pythagorean fuzzy reducible weighted geometric MSM (PFRWGMSM) operator to fuse Pythagorean fuzzy assessment information. Meanwhile, several worthwhile properties and especial cases of the developed operators are explored at length. Afterwards, we develop a novel Pythagorean fuzzy entropy based upon knowledge measure to ascertain the weights of attribute. Furthermore, an extended weighted aggregated sum product assessment (WASPAS) method is developed by combining the PFRWMSM operator, PFRWGMSM operator and entropy to settle the decision problems of unknown weight information. The efficiency of the proffered method is demonstrated by a teaching quality evaluation issue, as well as the discussion of sensitivity analysis for decision outcomes. Consequently, a comparative study of the presented method with the extant Pythagorean fuzzy approaches is conducted to display the superiority of the propounded approach.

A structured framework for performance optimization using JBLTO, FCOPRAS and FCODAS methodologies

PurposeThe proposed hybridized framework provides a new performance optimization-based paradigm for analysing the failure behaviour of paneer unit (PU) in the dairy industry.Design/methodology/approachA novel fuzzy Jaya-based Lambda–Tau Optimization (JBLTO) approach-based mathematical modelling was developed for calculating various reliability indices of the considered unit. Failure mode and effect analysis (FMEA) was carried using qualitative information gathered from system's expert opinions. Fuzzy-complex proportional assessment (FCOPRAS) approach was integrated within FMEA to recognize the most critical failure causes associated with various subsystem/components.FindingsThe availability of the unit falls by 0.053% as the uncertainty level increases from ±15 to ±25% and further decreases to 0.323% as the uncertainty level increases from ±25 to ±60%. Failure causes, namely wearing in gears of gearbox (MST4), an impeller's cavitation and/or corrosion (CFP4), winding failure of electric motor (WS9), were recognized as the most critical failure causes with FCOPRAS final performance scores of 100, 100 and 100 and fuzzy combinative distance-based assessment (FCODAS) resultant assessment score of 0.5997, 1.1898 and 1.6135.Originality/valueJBLTO approach-based reliability results were compared with traditional particle swarm optimization-based Lambda–Tau (PSOBLT) and traditional fuzzy Lambda–Tau (FLT) approaches for confirming the downward trend in the system's availability. The ranking results of qualitative analysis are compared with the implementation of FCODAS technique. Sensitivity analysis was executed to evaluate the robustness of the proposed hybridized framework.

Modification of the Logarithm Methodology of Additive Weights (LMAW) by a Triangular Fuzzy Number and Its Application in Multi-Criteria Decision Making

The Logarithm Methodology of Additive Weights (LMAW) method is a very young method and in its basic form is defined for crisp values. In this paper, the LMAW method was improved by being modified with triangular fuzzy numbers. The modification significantly improved the capacity of the LMAW method to consider uncertainty in decision making. The special importance of the method is reflected in a relatively simple mathematical apparatus due to which it is possible to define, with high quality, weight coefficients of criteria and rank alternative solutions in uncertain environments. The method was tested in solving the problem of the location selection for a landing operations point (LOP) in combat operations of the army. The validation of the obtained results was performed: (1) by means of comparison with the Fuzzy Simple Additive Weighting (FSAW) Method, the Fuzzy Multi-Attributive Border Approximation area Comparison (FMABAC), the fuzzy Višekriterijumsko KOmpromisno Rangiranje (FVIKOR), the fuzzy COmpressed PRoportional ASsessment (FCOPRAS), and the fuzzy Multi Attributive Ideal-Real Comparative Analysis (FMAIRCA); (2) by means of sensitivity analysis by changing the weight coefficients of criteria; and (3) using simulation software. In comparison with other methods, the quality of the ranking of alternative solutions was confirmed, which highlighted the special importance of the fuzzy LMAW method relative to that of certain standard methods, respectively, the ones that are often used and confirmed in practice. On the other hand, the sensitivity analysis, including the changing of the weight coefficients of criteria, showed that the model could tolerate smaller errors in defining the weight coefficients of criteria, and it provided stable results. Finally, the validation of results achieved with the use of simulation software confirmed the obtained output results. The output results confirmed the quality of the modified method.

Investigating the sustainable development goals derived due to adoption of circular economy practices

Recently, the novel concept of the circular supply chain (CSC) has gained substantial attention amongst researchers across the globe. It is due to the issues of unsustainability in supply chain operation of manufacturing industry. CSC amalgamates the circular economy (CE) into the supply chain of manufacturing organizations. Business organizations can achieve several sustainable development goals by adopting CSC as an innovative strategy. However, limited attention has been given to its implementation in emerging economies. Thus, this research aim is to identify and analyze the essential CE practices that help to accomplish the several sustainable development goals (SDGs) of CSC management. This research presents an integrated framework of Pythagorean fuzzy analytic hierarchy process (PF-AHP) and Pythagorean fuzzy combinative distance-based assessment (PF-CODAS) techniques. PF-AHP is employed to determine the relative importance of CE practices, whereas PF-CODAS method ranks the SDGs derived due to the adoption of CE practices. The effectiveness of the proposed framework is validated with the help of an Indian manufacturing organization. The finding of this research reveals that practices based on 'government', 'management', and 'economy' initiatives play a significant role and contribute 50 % of its influence on the effective CSC adoption, whereas, 'mitigate waste and enhance environmental sustainability', is identified as the most critical SDG realized due to adoption of CE practices. Sensitivity analysis is conducted to check the robustness of proposed methods. This research provides the systematic, accurate, and valuable decision support tools to practitioners to execute the CE practices efficiently for achieving the various sustainability goals.

A Fuzzy Decision-Making Framework for Route Selection in Multimodal Transportation Networks

This study presents a novel decision-making framework for route selection in multimodal transportation networks under fuzzy environments. The proposed framework integrates the fuzzy group decision-making technique, the fuzzy deliberate process, and fuzzy multiple criteria decision-making approaches. Hence, the fuzzy Delphi method, fuzzy risk assessment, the fuzzy analytic hierarchy process, and the fuzzy technique for order of preference by similarity to ideal solution are first combined to select the most appropriate multimodal route. An empirical study demonstrates that the proposed framework is an outstanding and systematic decision support tool to aid decision makers in transportation decision-making processes of freight route selections.

Fuzzy Bayesian Estimation of Linear (Circular) Consecutive k-out-of-n: F System Reliability

The consecutive k-out-of-n: F structure is broadly applicable in industrial and military frameworks. Without lifetime information about the entire design, it is appealing to use fuzzy earlier beliefs on its segments. In this paper the fuzzy Bayesian reliability assessment of the linear (circular) consecutive k-out-of-n: F system is proposed under the squared error loss function. The parameters are known as fuzzy random variables in the process of obtaining fuzzy Bayesian reliability. The conventional strategy for estimating Bayesian reliability will be utilized to construct the fuzzy Bayesian point estimator of the proposed system by applying the Resolution Identity theorem. A comparative study of the derived result with the literature is presented.
 HIGHLIGHTS
 
 Reliability Estimate of Consecutive k-out-of-n: F system
 Parameters are known as fuzzy random variables
 Applied Resolution Identity Theorem to estimate fuzzy Bayesian reliability
 Fuzzy Bayesian system reliability is calculated
 Fuzzy mean time to failure is calculated
 
 GRAPHICAL ABSTRACT

A Divergence-Based Medical Decision-Making Process of COVID-19 Diagnosis

This study is concerned with introducing a class of parametric and symmetric divergence measures under hesitant fuzzy environment. The proposed divergence measures have several interesting properties which make their use attractive. In order for exploring the features of proposed divergence measures for hesitant fuzzy sets (HFSs), we compare them with other existing ones in terms of divergence-initiated weighs and counter-intuitive cases. In the process of comparison, we first modify the conventional framework of hesitant fuzzy additive ratio assessment (HFARAS) using the proposed divergence measures, and then, the superiority of proposed measures is further demonstrated in a COVID-19 case study. There, we notify that the other existing divergence measures may not provide satisfactory results.

USING THE SUSTAINABILITY-BALANCED SCORECARD FOR ASSESSING SUSTAINABILITY ISSUES OF THE GREEN ENERGY COMPANIES

Assessing the sustainability issues of the green energy companies is a multiple criterion decision that includes both quantitative and qualitative elements. The sustainability-balanced scorecard (SBSC) for sustainability evaluation is more difficult than an internal evaluation and it requires more serious investigation in the green energy companies. This paper objectives to mix this sustainability evaluation and use fuzzy information with the SBSC. The study presents a fuzzy DEMATEL (decision-making trial and evaluation laboratory) method to develop an assessment model that integrates triangular fuzzy numbers, and DEMATEL to develop a fuzzy assessment, which prioritizes the relative influence of SBSC for green energy companies’ elements. First, this paper conducts a literature review on SBSC regarding sustainability issues to generate 15 elements with five aspects, which are used to measure the sustainability assessment. Next, fuzzy DEMATEL is employed to manage the uncertain linguistic terms, then to set up an influential network relationship map (INRM). This suggested model provides a structure for the related green energy companies to select the evaluation method and could arrange the sustainability approach according to future competitive pressure. The result shows that environmental aspect is the most direct effect and social aspect is the most important effect aspect to the other aspects.

Expert model of risk assessment for the selected components of smart city concept: From safe time to pandemics as COVID-19

The purpose of the paper is to create an information, fuzzy risk assessment model to support the decision-making of Municipality management for the establishment and management of measures in the safe mode (regular) of City, emergency and disaster situations, in the selected components of Smart City concept. Research on this topic was motivated by the need for support, especially in emergency situations, such as the COVID-19 pandemic. It is proposed that the evaluation be carried out at local level within the framework of the Smart City concept and selected components integrated into the entity, including the Smart Security, Smart Healthcare, and Smart Environment components supported by the Smart WebGIS subsystem. The model also assesses proposed solutions for self-government financing to ensure the acceptable risk, and economic impact of decisions on the city budget within the Smart Budget aspects of selected components. Decision-making is based on intellectual analysis, processing of fuzzy data and use of fuzzy inference. The output of the model is the assessment of the risk of the municipality subsystems, taking into account the threshold for the functioning of the municipality subsystems, the linguistic interpretation of the level of risk and the acceptability of the tolerable risk resource. The model algorithm was used to create a web application to support the Municipal management for the above-mentioned agenda, from safe time to pandemics.

Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid

Grid-connection of renewable energy microgrids (GCREM) is an important form of promoting the use of clean and renewable energy (RE). However, GCREM will bring huge risks to the power grid. Accurate evaluation and control of risks are critical to the development of GCREM. The existing research is not deep and comprehensive enough to make a reliable evaluation on the risks. The current study proposes a new evaluation framework based on the unit decomposition of the system of GCREM, and then builds a holistic fuzzy hierarchy-cloud assessment model for the risks. The main contributions of this paper are as follows: (1) decomposes GCREM risks to each functional unit of the system, and clarifies the risk transmission between the units within the system; (2) improves the accuracy of weighting risk variables based on interval type-2 fuzzy method; (3) realizes the visibility of risk evaluation and a prior judgment on its effectiveness; (4) establishes a 5-dimensional risk evaluation system of GCREM for the first time, which achieved full coverage of risk variables without the overlap between dimensions. The empirical analyses show that our model can not only assess the overall risk level of GCREM, but also identify key risk sources.

An Integrated Multi-criteria Structural Equation Model for Green Supplier Selection

The aims of the current study are to determine the criteria to be considered in a green supplier selection (GSS) process, develop an integrated decision-making approach using structural equation modelling (SEM) and fuzzy additive ratio assessment (ARAS) techniques to rank suitable suppliers, and investigate the effectiveness of this approach in collective decision-making. The study’s ultimate objective is to propose a method created from the perspective of fuzzy logic in which criterion weights are determined using SEM to resolve decision-making challenges such as GSS, in which a compromise solution is desired. In the first stage of the study, relevant literature as examined in detail. Eight main criteria and 27 sub-criteria were detected, taking into account classical, green, and social supplier selection (SS) criteria. A questionnaire was administered to 254 participants who were actively involved in SS processes for their companies, and the data were analyzed using SEM. In the second phase, six suppliers were evaluated considering the criteria found to have a positive impact on GSS, and fuzzy ARAS was applied. The results showed that the factors affecting GSS are quality (0.291), social responsibility (0.222), service (0.21), cost (0.149) and green product (0.128). The study presents an effective, objective, and fast method that can be used in decision-making problems such as GSS, that prevents potential loss of information and lack of transparency through an integrated approach, and that can be tested with a generalizable framework. The proposed hybrid method is an efficient and practical approach that can be tested on many decision-making problems, such as SS.

Pythagorean fuzzy entropy measure-based complex proportional assessment technique for solving multi-criteria healthcare waste treatment problem.

With the increasing risk to human health and environmental issues, the selection of appropriate management and treatment of healthcare waste has become a major problem, especially in developing countries. There are various alternatives to dispose of health care waste. The important is to assess the best alternative among them. The assessment of each alternative should be done based on public health, psychological, economic, environmental, technological, and operational aspect. The selection of the best health care waste treatment (HCWT) alternative is a complicated, multi-criteria decision-making (MCDM) problem involving numerous disparate qualitative and quantitative features. Hence, in this research article, the MCDM method is presented for estimating and choosing the best alternative of HCWT by COPRAS technique in a Pythagorean fuzzy set (PFS). Here, in this paper, first of all, a new entropy measure on PFSs is proposed and its validity is studied. Thereafter, the MCDM technique Complex Proportional Assessment (COPRAS) is discussed in which the criteria weights are assessed by the proposed entropy measure and score function to enhance an efficacy and efficiency of the proposed technique. Furthermore, the above-defined technique is employed to resolve the real-life problem to obtain the best treatment alternative to disposal of the health care waste. Finally, sensitivity analysis is presented to rationale the proposed viewpoint for prioritizing HCWT alternatives.

An Adaptive Fuzzy Multi-Criteria Model for Sustainability Assessment of Sugarcane Agroindustry Supply Chain

Supply chain sustainability assessment is key to maintaining and improving the performance of agroindustry supply chains, particularly in sustainable agroindustry development. The assessment of agro-industrial supply chain performance is a complex and dynamic process. Hence, there is a need for an adaptive fuzzy multi-criteria sustainability assessment model as an alternative method of analysis and improvement. This study aimed to design an adaptive fuzzy multi-criteria sustainability assessment and improvement model for the sugarcane agroindustry supply chain. In this study: (1) a fuzzy inference system (FIS) was developed to assess the performance of the sustainability dimensions. This study proposed 24 indicators for four dimensions: economic, social, environmental, and resource. (2) An adaptive neuro-fuzzy inference system (ANFIS) is designed to aggregate the overall supply chain sustainability performance. (3) The proposed fuzzy multi-criteria assessment model was compared with the common multidimensional scaling (MDS) and linear models. This study proved that the proposed synthesis of the FIS and ANFIS models is powerful and adaptive for evaluating supply chain sustainability and providing accurate results. (4) The strategies to improve sustainability performance were developed using the cosine amplitude method (CAM). The proposed model determined that the overall supply chain sustainability value was 68.58%, which was almost sustainable. Several strategies have been suggested to improve sustainability performance, including maintaining the sugarcane supply by strengthening the partnership program and improving the mill’s overall recovery, followed by factory revitalization or new factory investment.

A Sensitive Wavebands Identification System for Smart Farming

Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture. It helps the farmers in the optimal use of fertilizers. It reduces the cost of food production and also the negative environmental impacts on atmosphere and water bodies due to indiscriminate dosage of fertilizers. The traditional chemical-based laboratory soil analysis methods do not serve the purpose as they are hardly suitable for site specific soil management. Moreover, the spectral range used in the chemical-based laboratory soil analysis may be of 350–2500 nm, which leads to redundancy and confusion. Developing sensors based on the discovery of spectral wavebands that respond to soil macronutrient concentrations, on the other hand, is an innovative and successful technology since the results are dependable and timely. The goal of this article is to use a supervised neuro-fuzzy based dimensionality reduction approach in the sensor development process to determine sensitive wavebands of soil macronutrients. Accordingly, the spectral signatures of the soil are collected in an outdoor environment and mapped with its macronutrient concentrations. In this spectral analysis, the spectral reflectance of 424 wavelengths has been obtained and these wavelengths are evaluated through combined and individual modes as well. Appropriate wavelengths are selected in each case by minimizing the fuzzy reflectance assessment index. The effectiveness of these selected wavelengths in each mode is validated by modeling the relation between the reduced reflectance space and each macronutrient concentration using Partial Least Squares Multi Variable Regression (PLS-MVR) method. Set of optimal wavebands are identified and the results are compared with the existing systems.

Risk assessment method for power grid communication link failure based on fuzzy comprehensive assessment

Risk assessment method for power grid communication link failure based on fuzzy comprehensive assessment

Fuzzy FMEA risk assessment approach for IFF system in military helicopters using Matlab R2022A

In this article, the author reviews the fuzzy Failure Mode and Effect Analysis (fuzzy FMEA) as one of the effective methods of risk assess- ment. Using the fuzzy logic toolbox of the MATLAB R2022a software, the Identification Friend or Foe (IFF) system of military helicopters is analysed in a case study, during which the fuzzy risk priority numbers (F-RPN) for this system of military helicopters is created. Finally, the author of this paper summarizes the results obtained.

Selecting a green supplier utilizing the new fuzzy voting model and the fuzzy combinative distance-based assessment method

• In this paper, the selection of a Green Supplier is performed using a new hybrid Multi Attribute Decision Making-Data Envelopment Analysis method. • The fuzzy version of the Preferential Voting model is designed in this paper. • A new secondary goal model using the Combinative Distance-based Assessment method is proposed in the Cross Efficiency ranking method. • The proposed new method for Selecting a Green Supplier in an Automotive Group has been implemented. Significant increase in environmental concerns has led organizations to consider the necessary measures to apply green supply chain management to improve their environmental and economic performance. An important way to implement green supply chain management is to revise the methods of purchasing and selecting green suppliers. In this paper, a new fuzzy Data Envelopment Analysis (DEA) model for green supplier selection by collecting expert votes is presented. Then a way to improve the cross-efficiency method to achieve a complete ranking is suggested. In the improved method, a new secondary goal model based on the concepts of the Fuzzy COmbinative Distance-based ASsessment (CODAS) method will be presented. The proposed models were then used to select a green supplier in an automotive group. In the present case study, a complete ranking for green suppliers is obtained.

R-Set COPRAS (R-COPRAS) Methods-Based Multi-Attribute Decision-Making With RBM and RGBM Operators: A Case Study of Smart Mine Project Safety Assessment

The R-set is modeled by considering the risks associated with sources of information and future events. In the current work, there is no research on the aggregation operator of the R-set, and no in-depth research on its multi-attribute decision-making (MADM) methods. In order to extend the application of R-set more widely, this paper aims to propose a new risk-based fuzzy complex proportional assessment (R-COPRAS) method. First, the R-set Bonferroni mean (RBM) operator and the R-set geometric Bonferroni mean (RGBM) operator are investigated. Then, the correlation properties of these operators are studied. Based on these two operators, COPRAS methods in R-set environment are proposed, which consider the decision risk and can provide stable decision results. Ultimately, a smart mine safety assessment project is proposed to test and check the accuracy and effectiveness of the proposed R-COPRAS methods.