Fuzzy Analytic Hierarchy Process Method Research Articles

Fuzzy Multi-Criteria Decision for Geoinformation System-Based Offshore Wind Farm Positioning in Croatia

Renewable energy is one of the main components of a sustainable world and its future. The consumption of electricity from renewable sources in Croatia has an impressive rate of 53.5%, but offshore wind turbines (OWT) have not yet been installed in the Adriatic Sea. The aim of this study is to determine the possibilities for offshore wind farm (OWF) positioning in the Croatian part of the Adriatic Sea using marine spatial planning (MSP). Initial research to determine the points of interest was conducted based on wind speed. The authors established ten possible points for further research. Subsequently, different parameters were used as inputs for exclusion. The Fuzzy Analytic Hierarchy Process (AHP) method was used to calculate the weighting coefficients for a suitable set of criteria, exactly six of them. Using a combination of geoinformation system (GIS) analysis and weighting coefficients established through Fuzzy AHP, four points were established as suitable for OWF installation in Croatia. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used to select the best order for OWF positioning in the eastern part of the Adriatic Sea. To conclude, there are not many options for OWF positioning in Croatia. Furthermore, it is clear that they exist and should be explored further.

Fuzzy Method to Improve Products and Processes Considering the Approach of Sustainable Development (FQE-SD Method)

Assumptions of the concept of sustainable development should include actions towards the development of modern, well-managed enterprises. However, making decisions in this area is difficult as it often results from subjective assessments of environmental problems. Hence, there is a motivation to develop a method of analysing the search for solutions to environmental problems that supports decisions in the area of improving the quality of products or processes while considering their impacts on the natural environment. In view of the specification of this problem, it was considered that this method should be conducted in a fuzzy decision environment. This method is called FQE-SD (fuzzy qualitatively environmentally sustainable development). This method integrated, in a hybrid way, the selected tools or elements of qualitative and multi-criteria decision methods, i.e., using the SMARTER method, brainstorming (BM), a method to select the team of experts, the Pareto-Lorenz analysis, the fuzzy QE-FMEA method, and the fuzzy AHP method. The main contribution of the FQE-SD method is its hybrid methodology, which supports: (i) a coherent and objective approach during the identification, analyses, and ranking of the causes of incompatibility of products or processes and (ii) the realization of the sustainable development of products or processes. The method was tested using the magnetic-powder test (MT). This control was carried out for producers of an outer bearing made fromAMS6470 steel. The results of this work confirmed the practical possibilities of applying the FQE-SD method. This method can also be applied to other production situations, if appropriate assumptions are made.

Analisis Perankingan Supplier Bahan Baku Methanol Dengan Metode Fuzzy Analitycal Hierarchy Process (FAHP) Di PT XYZ

This study uses the Fuzzy Analytical Hierarchy Process (FAHP) method to examine the choice of methanol raw material sources at PT XYZ. The procedure of gathering primary and secondary data for this study entails identifying supplier selection criteria, compiling data on criteria and sub-criteria, and compiling information on supplier performance. Results indicated that product quality, price, supply reliability, sustainability, and reputation were important factors in PT XYZ's decision to choose a certain supplier for its methanol raw materials. The relative weight of each criterion and sub-criteria has been computed using the FAHP approach, which aids in assessing possible providers. Additionally, depending on the obtained priority values, supplier rankings are also established. In conclusion, PT XYZ may choose its raw material suppliers for methanol using the FAHP approach effectively. As well as producing more objective and organized outcomes, this strategy aids in lowering decision-making uncertainty and complexity.

Characterization of the Coastal Vulnerability in Different Geological Settings: A Comparative Study on Kerala and Tamil Nadu Coasts Using FuzzyAHP

The acceleration of coastal processes is manifested in the form of coastal erosion, average sea level rise, drastic changes in coastlines, and more turbulent ocean waters. In this study, the coasts of Kerala and Tamil Nadu, India, were selected to identify the effects of increasing coastal processes. Therefore, it is necessary to identify and map vulnerable areas by taking into account the key parameters, such as topographical and socio-economic factors, to relate to coastal processes. The fuzzy Analytical Hierarchy Process (AHP) method was employed to identify the most vulnerable zones. The key findings revealed that about 14% and 2% of the coast of Tamil Nadu and Kerala, respectively, are classified under the physically highly vulnerable category. Similarly, ~17% and ~30% of coastal Tamil Nadu and Kerala, respectively, are highly socially vulnerable. The overall vulnerability assessment showed that 7–8% of both coastal areas were highly vulnerable. We concluded that the Thiruvallur, Chennai, Kanchipuram, Cuddalore, and Nagapattinam coasts on the east coast and the Malappuram, Thrissur, Ernakulam, Alappuzha, and Kollam coasts on the west coast were very highly vulnerable to coastal processes. Identifying vulnerable zones helps to better understand the impacts of rapid coastal processes and, with this prior estimation, the policymakers can take necessary actions to mitigate the irreversible impacts of coastal processes.

Flood susceptibility mapping using fuzzy analytical hierarchy process for Cedar Rapids, Iowa

ABSTRACT Floods affect over 2.2 billion people worldwide, and their frequency is increasing at an alarming rate compared to other disasters. Presidential disaster declarations have issued increasingly almost every year in Iowa for the past 30 years, indicating that the state is on the rise of flood risk. A multi-disciplinary approach is required, in which the underlying hydrologic processes that cause floods are closely linked with watershed-level socio-economic functions using effective collaboration tools to ensure community participation in the co-production of mitigation plans while paying attention to socio-environmental justice principles. Considering the existing limitations and needs, we conducted a flood risk assessment by utilizing geophysical and socio-economic datasets for a case study in Cedar Rapids, Iowa. Flood risk outputs are generated based on three main risk groups: geophysical-based flood risk, socioeconomic risk, and combined flood risk. An extensive literature review is conducted to determine the pairwise comparison matrices for the parameters that are used in the analytical hierarchy process (AHP) and fuzzy AHP methods. Our results indicate that high- and very-high-risk flood susceptibility zones are primarily located in central urban areas with lower elevations, regardless of the method type (AHP or FAHP). According to overall results, a large area of Cedar Rapids consists of a medium risk level according to the flood risk map combined with the fuzzy AHP method. The results show that high and very high-risk areas are 16% of the studied region, medium, low and very low-risk areas correspond to 84%. Besides, nearly 40% of the population lives in high to very high flood risk zones.

Evaluating and prioritizing the carbon credit financing risks and strategies for sustainable carbon markets in China

Carbon markets are crucial to attaining sustainable development objectives given the pressing need to cut greenhouse gas emissions and combat climate change. China is a key player in the fight against climate change since the country emits the most greenhouse emissions globally. In light of China's carbon markets, this study evaluates the risks and mitigation strategies related to financing carbon credit projects. Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Viekriterijumsko Kompromisno Rangiranj (FVIKOR) methodologies are used to assess carbon finacing risks and strategies for the growth of China's carbon market. The FAHP method evaluated carbon credit financing risks and sub-risks, while the FVIKOR method prioritized mitigation strategies. The findings of the FAHP method show that regulatory and policy risks, financial risks, and operational risks are the major risks in the Chinese carbon markets. To mitigate these risks, prioritizing strategies based on FVIKOR suggests that developing stakeholder relationships, financial stability, and transparency would be a practical approach to achieving efficient, productive, and sustainable carbon markets in China. The study provides practical policy implications for stakeholders involved in carbon credit financing and contributes to global climate change efforts by offering insights into carbon credit market risks and opportunities.

Bus type selection with fuzzy approach for public transportation

There is tightening political pressure on cities to publish zero-emission strategies to decrease greenhouse emissions. To achieve these targets, decreasing public transportation emissions has become critical. There are different types of green transportation such as electric, compressed natural gas, hydrogen, biofuel, etc. This study develops a model regarding a holistic view that not only focuses on economic and operational conditions but also on business and strategy to decide the best bus type for public transportation for Istanbul metropolitan area. To handle the vagueness and complexity of the problem, the Spherical Fuzzy AHP method is applied to the model, as the method can handle three membership functions, which are membership, non-membership, and hesitancy. Also, to compare the results a classical AHP is performed with the same data. Results show that the diesel bus type stands out as the best option for both methods regarding the chosen criteria for Istanbul. The others varied with respect to methods. This study sheds light on results that could vary regarding the country’s context such as economic, social, and political factors. Although there are lots of studies on vehicle selection problems by applying multi-criteria decision-making methods, many of them have not utilized Spherical Fuzzy Set. To test the proposed model, a real case study is conducted. From this point, this study will not only contribute to the literature but also inform decision-makers and practitioners in terms of prioritizing their selection criteria.

Factors influencing the effectiveness of blended learning activities: A case study of Vietnam National University, Hanoi

Blended learning (BL) is an increasingly important pedagogical approach that combines traditional classroom instruction with digital resources to enhance student engagement and learning experiences. This study aims to evaluate the factors that influence the effectiveness of teaching activities in a BL model. Four groups of factors with a total of 20 sub-factors are considered, including lecturer-related factor (6 sub-factors), student-related factor (6 sub-factors), organizational factor (4 sub-factors), and technology factor (4 sub-factors). To collect data, this study conducted interviews with experts and managers who have extensive experience in managing training activities at Vietnam National University, Hanoi. The generalized fuzzy analytic hierarchy process (AHP) method is applied to evaluate the effectiveness of BL activities at VNU-Hanoi. The results revealed that lecturer-related factors have the most significant impact on the effectiveness of BL activities at VNU-Hanoi, followed by technology, organizational, and student-related factors. These findings highlight the importance of supporting and preparing lecturers to deliver effective BL experiences.

PRIORITIZATION OF OVERALL SUSTAINABILITY FACTORS OF CLOUD MANUFACTURING THROUGH AHP AND FUZZY AHP APPROACH

In this global competitive environment, with the recent advancement in information and communication technologies, the industries are adopting new strategies to sustain. Cloud manufacturing is a new technology that utilizes data analytics for better decision-making resulting in more productive, cost, and energy-efficient operations. Increasing awareness towards a clean environment and optimum utilization of resources in manufacturing motivate us to study cloud manufacturing in the context of sustainability. Therefore, a significant number of social, environmental, and economic factors of cloud manufacturing are identified through literature review, and experts’ opinions and prioritization of these factors are obtained through the AHP and Fuzzy AHP methods. As per the final results obtained, “Efficient use of resources” is the most significant factor for the adoption of cloud manufacturing process and “Remote material monitoring” is the least significant factor amongst all the factors taken under consideration. The results are found to be consistent and accurate as per the value of consistency ratio. And the percentage obtained for social, environmental, and economic factors proves the cloud manufacturing process to be a sustainable manufacturing process.

Identifying Critical Stations Affecting Vulnerability of a Metro Network Considering Passenger Flow and Cascading Failure: Case of Xi’an Metro in China

Analyzing the importance grade of each metro station is the premise and foundation to ensure the safe and efficient operation of the metro network. This paper explores the identification method of critical stations in the metro network on the basis of considering the influence of passenger flow. Eight indicators were selected from both the static and dynamic aspects to construct the critical station identification index system considering the impact of passenger flow and cascading failure. Then, the triangular fuzzy analytic hierarchy process (TFAHP) method and critical importance through intercriteria correlation (CRITIC) method were used to calculate subjective and objective weight of all indicators, and the combined weighting method based on game theory was applied to calculate the comprehensive weight. The improved technique for order of preference by similarity to ideal solution (TOPSIS) method was developed to calculate the station importance and rank all stations according to their importance. Finally, the Xi’an metro network by mid-2021 was taken as the case study. The results show that there are 21 critical stations in the Xi’an metro network in three time periods (i.e., morning rush hours, evening rush hours, and nonrush hours) on weekdays and weekends, respectively, and those critical stations are divided into three levels. High centrality, high passenger flow intensity, and strong destructive ability are three important characteristics of critical stations in the metro network, and different critical stations have different importance characteristics. The Xi’an metro operation management authority needs to conduct a classification management scheme for those critical stations. The conclusions can provide the basis for the metro operation management authority to formulate accurate station management scheme, so as to increase the robustness of the metro network.

Development and validation of a biological risk assessment tool among hospital personnel under COVID-19 pandemic conditions.

The need for a biological disease risk assessment method to prevent the contagion of these diseases, particularly among healthcare personnel, is crucial. Therefore, this study aimed to develop and validate a biological risk assessment tool for biological agents among hospital personnel under COVID-19 conditions. This cross-sectional study was performed on 301 employees in two hospitals. Firstly, we identified the items affecting the contagion of biological agents. Then, we computed the weight of the items using the Fuzzy Analytical Hierarchy Process (FAHP) method. We used the identified items and the estimated weights in the next step to develop a predictive equation. The outcome of this tool was the risk score of biological disease contagion. After that, we used the developed method to evaluate the biological risk of the participants. The ROC curve was also used to reveal accuracy of developed method. In this study, 29 items were identified and categorized into five dimensions, including environmental items, ventilation items, job items, equipment-related items, and organizational items. The weights of these dimensions were estimated at 0.172, 0.196, 0.255, 0.233, and 0.144, respectively. The final weight of items was used to develop a predictive equation. The area under ROC curves (AUC) was also calculated as 0.762 (95% CI: 0.704, 0.820) (p<0.001). The tools developed using these items had acceptable diagnostic accuracy for predicting the risk of biological diseases in health care. Therefore, one can apply it in identifying persons exposed to dangerous conditions.

Pythagorean Fuzzy AHP Based Dynamic Subcontractor Management Framework

In construction projects, a significant part of construction work is done by subcontractors (SCs). Therefore, their management by main contractors (MCs) becomes an important issue as the density of SCs is created at the construction sites. In recent years, more focus on SC evaluation and selection in bidding process has been on the agenda whereas the subject of SC performance appraisal on-site during the project execution phase has been untended in the literature. Thus, this study aims to focus on the measurement and evaluation of the performance of SCs in the project execution phase, and to provide a tentative performance-based dynamic management framework that MCs will use in the management of SCs in order to take proactive measures. In line with the aim, a total number of 23 performance measurement criteria (PMC) under 7 main groups were determined as a result of a comprehensive literature review and expert evaluations. Knowing that not every criterion will have the same effect in performance measurement, pairwise comparisons of the criteria were made using the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) method and their importance weights were determined. The PFAHP method was obtained by integrating the Pythagorean fuzzy set into the AHP method and chosen with the aim of improving the fuzzy AHP method and obtaining more consistent results by eliminating the uncertainty since Pythagorean fuzzy sets is more capable than fuzzy sets at expressing and handling uncertainty in uncertain environments. Lastly, a framework for SC performance measurement and evaluation on project execution phase is presented. It is believed that the presented framework will allow for a proactive management style that will enable effective decisions to be made while the project is ongoing, and a dynamic way of working instead of static and conventional work.

Prioritizing risk factors of hazardous material road transportation accidents using the fuzzy AHP method.

Annually, large amounts of hazardous materials (hazmat) are transported through the roads and this movement causes various accidents. Identifying the causes of these accidents is a critical issue for all public governments. This study aimed to identify the effective risk factors for hazmat road transport accidents and determine their relative weight using the fuzzy analytical hierarchy process (AHP) method. This qualitative study was conducted in 2021 in Iran and included four steps, i.e., the identification (using literature review and semi-structured interview), determination (according to the expert panel opinion), classification, and prioritization of effective factors in hazmat road transportation accidents. To prioritize and determine the relative weight of the effective factors, the fuzzy AHP technique was used. In total, 159 risk factors were identified, which were classified into six factors (including road, transportation management, vehicle, cargo, driver, and weather conditions) and 24 sub-factors. The main factor (greatest relative weight) with the highest priority was the driver (0.181). The road (0.167), cargo (0.166), vehicle (0.169), transportation management (0.161), and weather conditions (0.159) were the next priorities, in that order. The results demonstrated that the driver is the most important factor in causing accidents when transporting hazmat by road. The findings of this study might have the potential to decrease the frequency and consequence of accidents caused by the road transport of hazmat.

Evaluating barriers and strategies to green energy innovations for sustainable development: developing resilient energy systems

Achieving sustainable development and reducing climate change require a shift to green energy sources. Yet, switching to green energy sources necessitates substantial research and development, as well as regulatory and policy adjustments. Additionally, a number of obstacles are impeding the development of green energy innovation. This study identified several key barriers and sub-barriers that obstruct the development of green energy innovation. Thus, this study identified multiple strategies to overcome those barriers. Therefore, this study uses the fuzzy Analytical Hierarchy Process (AHP) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods to assess and rank the barriers and strategies to building resilient energy systems in China. First, the fuzzy AHP method identifies the four barriers and sixteen sub-barriers, while the fuzzy TOPSIS method classifies six strategies for the green energy innovation system in China. According to AHP results, funding and policy constraints are the most crucial barriers to green energy innovation. The fuzzy TOPSIS findings show that providing incentives for green energy investment and strengthening policy implementation and enforcement are the most significant strategies for overcoming the barriers to green energy projects.

A FUZZY ANALYTICAL HIERARCHY PROCESS FOR EVALUATION OF KNOWLEDGE MANAGEMENT EFFECTIVENESS IN RESEARCH CENTERS

Measuring knowledge management (KM) effectiveness is a very important issue in organizations today. This study aims to develop a method to evaluate the effectiveness of KM under uncertainty in research centers (RCs) in Iran. To develop an evaluation, the relevant literature was reviewed to identify KM effectiveness criteria. Next, the judgments of the experts, specialists, scholars, and professionals in IT and KM systems and senior managers of Iran’s RCs were determined using a pairwise comparison questionnaire. Because linguistic terms are an integral part of human judgments that will influence the results of the research, a fuzzy Analytic Hierarchy Process (AHP) called the Extent Analysis (EA) method was used for data analysis and weight determination. Accordingly, 34 subcriteria extracted from the literature that are important in the evaluation of KM effectiveness were categorized into six main criteria as follows: human resources, leadership and center structure, knowledge creation and acquisition, knowledge storage and security, knowledge sharing, and knowledge utilization and updating. The findings indicate that human resources is the most important criterion based on both the AHP and fuzzy AHP methods. The other five criteria in descending order of importance are knowledge sharing, leadership and center structure, knowledge utilization and updating, knowledge creation and acquisition and knowledge storage and security. Finally, to test the validity and reliability of the proposed framework, we evaluated the effectiveness of KM system in nine of Iran’s RCs.

RAGOSRA: Rough attributed goal oriented software requirements analysis method

Goal oriented software requirements analysis method is used for the analysis of elicited functional goals (FGs) and non-functional goals (NFGs) of a system in which goals are decomposed and refined into sub-goals until requirements from the sub-goals are identified. Based on the critical analysis, we found that most of the attention of goal-oriented methods is on the crisp and fuzzy logic during the analysis of the software goals or requirements. In these methods’ prior information about the type of membership function is required; and the selection of membership function depends on the subjective justification. As a result, it lacks objectivity and may affect the ranking values of the goals or requirements during the analysis. Therefore, this paper presents a rough attributed goal-oriented software requirements analysis (RAGOSRA) method in which rough preference matrix has been used to capture the opinions of different stakeholders. The results of the RAGOSRA method are compared by considering the following criteria, i.e., goal types, goal links, types of data used in the analysis, stakeholder perceptions and time complexity with some fuzzy based methods. Based on the time complexity analysis, it is found that RAGOSRA method requires only 24 operations for the selection of goals for the dataset having 3 NFGs and 4 FGs of an institute examination system. On the other hand, FAGOSRA method, fuzzy TOPSIS method, and fuzzy AHP method requires 36, 166, and 240 operations respectively.

Feasibility of fuzzy analytical hierarchy process (FAHP) and fuzzy TOPSIS methods to assess the most sensitive soil attributes against land use change

Feasibility of fuzzy analytical hierarchy process (FAHP) and fuzzy TOPSIS methods to assess the most sensitive soil attributes against land use change

Analisis Pemilihan Supplier Bahan Baku Edamame Dengan Metode Fuzzy Analitycal Hierarchy Process (FAHP) Di PT XYZ

This study aims to analyze the selection of edamame raw material suppliers at PT XYZ using the Fuzzy Analytical Hierarchy Process (FAHP) method. This research involves the process of collecting primary and secondary data which includes identification of supplier selection criteria, collection of criteria and sub-criteria data, and collection of supplier performance data. The results showed that the relevant supplier selection criteria in the context of edamame raw materials at PT XYZ were product quality, price, supply reliability, sustainability and reputation. Based on the FAHP method, the relative weight of each criterion and sub-criteria has been calculated, which helps in evaluating potential suppliers. In addition, supplier rankings are also determined based on the resulting priority values. In conclusion, the FAHP method can be used as an effective tool in selecting raw material suppliers for edamame at PT XYZ. This method helps in reducing uncertainty and complexity in decision making, as well as providing more objective and structured results.

Optimization the reliability of emergency safety barriers based on the subjective safety analysis and evidential reasoning theory. Case study

PurposeThis study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.Design/methodology/approachThe emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.FindingsA real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.Research limitations/implicationsThis study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.Originality/valueOur contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

Fuzzy analytic hierarchy process for pentagonal fuzzy numbers and its application in sustainable supplier selection

Different fuzzy analytic hierarchy process (FAHP) methods are typically developed for conventional fuzzy numbers (FNs), mainly triangular and trapezoidal FNs. The ascending and descending parts of triangular and trapezoidal membership functions (MFs) are straight lines. Therefore, if the value of a member increases by the same values, its membership degrees in ascending (descending) part increase (decrease) equally. These MFs do not necessarily reflect the experts' preferences. Consider two different cases; in the first one, the product quality of supplier A compared to supplier B increases from 2 to 3 times, and in the second case, this quality increases from 8 to 9 times. Triangular and trapezoidal membership degrees in both cases increase equally. However, the quality advantage of supplier A increases by 50% in the first case, while it increases by 12.5% in the second case. Therefore, the experts’ preferences may increase differently for these cases that cannot be reflected accurately by triangular and trapezoidal MFs. To overcome this flaw, we develop four FAHP methods for pentagonal FNs (PFNs). We also use an indirect method to defuzzify the fuzzy local weights. Indirect defuzzification is a simple method equivalent to the center of gravity (COG) method and needs low computations. Numerical examples are used to illustrate the proposed methods. A real example of ranking suppliers in a sustainable framework based on pentagonal fuzzy preferences is also presented. To extract crisp local weights from pentagonal fuzzy comparison matrices, we use the pentagonal FAHP methods presented in this study.