Fuzzy Analytic Hierarchy Process Technique Research Articles

Fuzzy Analytic Hierarchy Process–Technique for Order Preference by Similarity to Ideal Solution: A Hybrid Method for Assessing Vegetation Management Strategies under Electricity Distribution Lines to Prevent Deforestation Based on Ecosystem Service Criteria

This study evaluated vegetation management (VM) strategies under electricity distribution lines (EDLs) through ecosystem service (ES) criteria. Deforestation, worsened by insufficient VM practices, poses a threat to ecosystem stability. Using a hybrid FAHP (Fuzzy Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach, ten VM strategies were assessed based on 15 ES criteria. The FAHP results identified biodiversity, timber resources, and erosion control as the most crucial criteria due to their significant weights. The TOPSIS analysis determined that VM6 (creation and restoration of scrub edges) was the most effective strategy, achieving a value of 0.744 for reducing deforestation and enhancing energy security. VM6 helps preserve forest cover and protect infrastructure by creating a “V”-shaped structures within the EDLs corridor. This study underscores the importance of ES-oriented VM strategies for sustainable vegetation management and deforestation mitigation. It also highlights the need for incorporating scientific, ES-based decision support mechanisms into VM strategy development. Future research should expand stakeholder perspectives and conduct a comprehensive assessment of ESs to ensure that VM strategies align with ecological and socio-economic sustainability. This study provides a framework for improving VM practices and offers directions for future sustainable energy management research. This study focuses exclusively on ecological criteria for evaluating VM strategies, neglecting other dimensions. Future research should use methods like ANP and fuzzy cognitive maps to explore inter-dimension relationships and their strengths. Additionally, employing SWARA, PIPRECIA, ELECTRE, and PROMETHEE for ranking VM strategies is recommended.

Analyzing Factors Influencing the Development of Railway Freight Transportation Service through the Fuzzy Analytic Hierarchy Process Technique

The main objective of this study is to apply the Fuzzy Analytic Hierarchy Process (FAHP) technique to assess factors influencing the development of railway freight transportation services. These factors include four critical performance indicators within the supply chain: responsiveness, cost, reliability, and agility. Moreover, the study aims to develop guidelines for enhancing the effectiveness of railway freight transportation in Chiang Rai province, particularly through the Den Chai–Chiang Rai–Chiang Khong railway route. Data were collected from 9 experts, including logistics service providers, users, and academics then, pairwise comparisons of factors were conducted. The results revealed that the cost factor holds the highest significance at 33.86%, followed by reliability, responsiveness, and agility factors at 28.51%, 26.14%, and 11.49%, respectively. Consistent with satisfaction scores obtained from logistics service users, the cost factor holds the highest satisfaction score at 4.78, followed by reliability, responsiveness, and agility factors with scores of 4.41, 4.16, and 4.01, respectively. The result above will bring towards preparation in railway freight transportation of Chiang Rai province and encouraging entrepreneurs to shift to railway transportation mode in the end.

Leveraging Social Media to Gauge Public Opinion on Waste Electrical and Electronic Equipment Management

In recent years, the rapid advancement of technology has led to a significant increase in the global use of electrical and electronic devices. This has resulted in a surge in the generation of waste electrical and electronic equipment (WEEE), a critical component of the complex solid waste management process. Since consumers play a major role in generating WEEE, understanding their perspectives on WEEE disposal is essential for developing effective management strategies. This study employs a combined approach utilizing quantitative methods, such as the analysis of 2,905,579 Twitter tweets collected from May 2019 to April 2022, and the fuzzy analytic hierarchy process (FAHP) technique, to identify appropriate end-of-life (EOL) options for WEEE. While there have been numerous studies on factors influencing consumer participation in WEEE disposal programs, no prior research has focused on identifying suitable EOL options for WEEE. A review of the literature revealed that factors such as ease of access to recycling centers, awareness, distrust in governments, financial incentives, charitable contributions, and concerns about data disclosure influence consumers’ decisions to participate in WEEE disposal programs. Additionally, four EOL options, namely re-use, remanufacturing, recycling, and disposal, were suggested for these products. Subsequently, the FAHP technique was used to examine the relationships between these options, and a suitable EOL option was recommended for each factor. The findings of this research can serve as a valuable tool in the WEEE management process, aiding in the development of effective strategies for WEEE disposal and contributing to a more sustainable approach to handling electronic waste.

Demarcation of groundwater potential zones in Ponnai sub-basin, Southern India using remote sensing, GIS and fuzzy-AHP approaches

ABSTRACT Groundwater is an essential source for household, irrigation and industry needs. The amount of groundwater and its quality are rapidly declining because of urbanization and industrialization. Groundwater resources in hard rock regions should be handled properly to maximize their utilization. This work aims to demarcate the Groundwater Potential Zones (GWPZ) in a part of the Palar River Basin (Ponnai sub-basin) by combining Remote Sensing (RS), Geographic Information System (GIS) and Fuzzy-Analytical Hierarchy Process (FAHP). The factors which influence the groundwater like geology, land use/land cover (LULC), geomorphology, slope, soil, rainfall, lineament density (LD), drainage density (DD), normalized difference vegetation index (NDVI), topographic wetness index (TWI) and topographic position index (TPI) are considered for mapping of GWPZ. The weightage is allocated to these parameters on the basis of the FAHP technique and the obtained groundwater potential map was classified as, very poor (13.5%), poor (21.76%), moderate (31.5%), good (20.66%) and very good (8.54%). The GWPZ map was validated with the actual well yield of the Ponnai sub-basin. The research work will serve as a guideline for the effective use of groundwater and long-term sustainable management of the aquifer in the Ponnai sub-basin.

Critical success factors of blockchain technology adoption in banking and financial sector using diamond fuzzy AHP

Blockchain technology is creating significant interest among a wide range of industries in the world due to the continuing applications in the banking sector. Thus, the aim of this research is to introduce an outline for examining critical factors that affect the success of the adoption of Blockchain-technologies in the sector of Finance and arranges them using the fuzzy analytical hierarchy process technique. First, it identifies thirteen critical success factors under three categories: technological, organizational, and environmental, taking the assistance of the extensive literature review and expert-opinion. Then, these factors are given a ranking that is based on their relative weightage. It is concluded that top management attitude, organization readiness, government regulation, immutability, and disintermediation are the detrimental factors for widespread blockchain adoption. The findings of this study will empower the stakeholders in the financial sector to improve their performance using blockchain technologies.

Enhancing healthcare security measures in IoTT applications through a Hesitant Fuzzy-Based integrated approach

<abstract> <p>Due to their impact on transportation, Internet of Transportation Things (IoTT) devices have garnered attention recently. Their most notable use is in healthcare, where transportation has been significantly influenced by Internet of Things (IoT) devices. However, threats to infrastructure integrity, medical equipment vulnerabilities, encryption, data integrity threats, and various other security issues make these devices particularly vulnerable. They transmit a considerable amount of sensitive data via sensors and actuators. Given their susceptibility to various attacks, securing the application security of IoTT is crucial. Consequently, IoTT device-based applications must undergo thorough security screening before integration into the healthcare network. Additionally, the authentication technique employed must be robust and reliable. IoTT device evaluation should be impartial and take into account security risk issues. This study proposes an evaluation approach for IoTT devices that utilizes key security risk factors to ensure reliable and secure authentication. Employing hybrid multicriteria decision-making, the suggested strategy evaluates authentication features to select the optimal hospital information system. The hesitant fuzzy analytic hierarchy process-technique for order of preference by similarity to ideal solution (Hesitant Fuzzy AHP-TOPSIS) method is used to systematically examine security risks in a real-time case study with seven alternatives. Results indicate that mediXcel electronic medical records are the most viable, while the Caresoft hospital information system is the least viable, providing valuable insights for future studies and IoTT application professionals. This research addresses security issues to enhance patient data integrity and privacy, facilitating the seamless integration of IoTT applications into healthcare, particularly in emergency healthcare.</p> </abstract>

Sustainable planning and design for eco-industrial parks using integrated multi-objective optimization and fuzzy analytic hierarchy process

ABSTRACT The increasing growth of industrial facilities calls for sustainable planning and design. In this research, the multiple objective optimization model is developed to plan for Eco-Industrial Parks, in which economic, social, and environmental criteria are evaluated. Our proposed optimization model is integrated with the simulation-based risk profile based on emergency scenarios. Varied chemical substances and explosive locations are further analyzed to assess the impact of risk. Then, the Fuzzy Analytic Hierarchy Process technique is applied to examine uncertain decisions. Next, this study presents the proposed model with the case study of selective industrial-building types in an industrial park, in which industrial plants, hazardous material plants, warehouse buildings, and office space are included. Our analysis reveals that tradeoffs exist in designing an industrial estate with various industrial plants under conflicting objectives. Finally, tradeoffs are investigated using Pareto analysis resulting in sustainable planning for an industrial estate.

Examining and prioritizing the effect of sustainable energy on the job market to advance China's green workforce

China, the world's greatest emitter of greenhouse gases, has committed to reaching peak carbon dioxide emissions by 2030 and carbon neutrality by 2060. One strategy to accomplish this aim is switching to a low-carbon economy via advancing renewable energy (RE) projects. Therefore, this study focuses on solar, wind, biomass, and hydropower and examines the beneficial employment effects of RE projects in China. The study uses fuzzy-based Multi-Criteria Decision Making (MCDM) methodologies, such as the Analytical Hierarchy Process (AHP) and Weighted Aggregated Sum Product Assessment (WASPAS), to evaluate numerous employment effect criteria and sub-criteria. Based on these evaluations, the report prioritizes four main types of RE projects. According to the fuzzy AHP technique results, direct employment, skill requirements, and local employment are the most crucial employment effect factors. The study then employed the fuzzy WASPAS approach to assessing various RE initiatives' employment prospects. According to the findings, hydropower is the best choice for creating jobs, followed by wind and solar power initiatives. In recent years, the hydro, wind, and solar power industries have experienced rapid expansion, creating numerous job possibilities in production, installation, operation, and maintenance. Additionally, creating RE projects can boost regional economic growth and lessen poverty.

Ranking load in microgrid based on fuzzy analytic hierarchy process and technique for order of preference by similarity to ideal solution algorithm for load shedding problem

<span lang="EN-US">This paper proposes a method to rank the loads in the microgrid by means of a weight that combines the criteria together in terms of both technical and economic aspects. The fuzzy analytic hierarchy process technique for order of preference by similarity to ideal solution (fuzzy AHP TOPSIS) algorithm is used to calculate this combined weight. The criteria to be considered are load importance factor (LIF), voltage electrical distance (VED) and voltage sensitivity index (VSI). The fuzzy algorithm helps to fuzzy the judgment matrix of the analytic hierarchy process (AHP) method, making it easier to compare objects with each other and remove the uncertainty of the AHP method. The technique for order of preference by similarity to ideal solution (TOPSIS) algorithm is used to normalize the decision matrix, determine the positive and negative ideal solutions to calculate the index of proximity to the ideal solution, and finally rank all the alternatives. The combination of fuzzy AHP and TOPSIS algorithms is the optimal combination for decision making and ranking problems in a multi-criteria environment. The 19-bus microgrid system is applied to calculate and demonstrate the effectiveness of the proposed method.</span>

Developing an extended producer responsibility system for solid waste management in Jordan using multi-criteria decision-making approach.

To move from a traditional end of pipe approach into a more sustainable solid waste management system, the Jordanian Government has recently passed a set of new regulations The National Solid Waste Management Strategy has put a road map to encourage circular economy practices. One of the considered policy instruments is the adoption of the extended producer responsibility (EPR). The current study aimed to adopt a multi-criteria decision-making method to select the most convenient EPR structure within the Jordanian context. The study used analytical hierarchy process (AHP) and fuzzy AHP (FAHP) techniques to select the suitable type of producer responsibility organization (PRO) structure. A four-level hierarchy model was constructed with 4 criteria, 10 sub-criteria and 3 PRO alternatives. The analysis revealed that the legal and administrative criteria is the most important one (0.47) followed by environmental criteria (0.22), whereas the least important ones were socio-economic (0.17) and technical criteria (0.13). The most preferable PRO alternative was found to be PRO with profit. There were slight differences between all weight values under AHP and FAHP. Despite the availability of several laws, there is a need to develop the legal and administrative framework to enable the adoption of EPR in Jordan. Research should be the first step in the process of EPR system design. None of the previous studies conducted used the AHP and FAHP in assessing and selecting the EPR systems.

The factors obstructing the blockchain adoption in supply chain finance: a hybrid fuzzy DELPHI-AHP-DEMATEL approach

PurposeSupply chain finance (SCF) is an advanced financing solution for medium and small organizations. However, due to its nascent stage, SCF is still struggling with its application in the supply chain. The blockchain application in SCF can bring lots of opportunities and smart techniques to deal with financing to organizations. However, some factors restrict the proper adoption of blockchain in SCF. Therefore, this study aims to identify and analyze the factors obstructing blockchain adoption in SCF.Design/methodology/approachThe present study applied a hybrid fuzzy DELPHI-AHP-DEMATEL to validate and analyze the factors. The fuzzy Delphi techniques were adopted to validate the identified factors. Thereafter, the analytic hierarchy process (AHP) has been used to prioritize the validated factors. Further, the decision-making trial and evaluation laboratory (DEMATEL) method has opted to classify the factors into cause-and-effect groups.FindingsThe result of the study revealed that lack of technological competence and confidentiality leaking are the most prioritized factors and act as the prime factors for the obstacles in the blockchain application in the SCF. The application of the DEMATEL method revealed that the highest causing factor is authenticity, and the highest effecting factor is high cost.Practical implicationsThe current study enhances the knowledge and information of managers and policymakers about the challenges associated with the blockchain application in SCF as well as provides better insight to deal with various factors obstructing blockchain adoption in SCF.Originality/valueThe current study is the first of its kind, where factors obstructing blockchain adoption in SCF are identified and validated with the help of experts and practitioners by incorporating the fuzzy Delphi method. Thereafter, the validated factors are prioritized by using fuzzy AHP and fuzzy DEMATEL techniques helps to identify the cause-and-effect group, which opens the door for future research work.

Fostering a Sustainable Energy Future to Combat Climate Change: EESG Impacts of Green Economy Transitions

The transition to a green economy for any country is crucial for the sustainability development of the economy, environment, society, and governance (EESG). A green economy is a sustainable approach to combating climate change and promoting sustainable development through the adoption of sustainable energy. This research utilizes the Delphi and fuzzy analytical hierarchy process (AHP) methodologies to assess and rank the EESG criteria and policy options for transitions to a green economy. The factors and policy choices are identified using the Delphi approach for further analysis. These factors and policy alternatives for switching to a green economy for sustainable development are determined using the fuzzy AHP technique. According to the fuzzy AHP approach, environmental, social, and economic factors are best suited for green economy transitions. The findings also show that the most crucial policy options for the switch to a green economy are research and development, carbon pricing, and renewable energy targets. The findings are useful to guide the creation of policies and the selection of options for the implementation of a green economy. Finally, the conclusion can guide actions to combat climate change and develop a sustainable energy future.

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.

Prioritization of Supply Chain Capabilities Using the FAHP Technique

With the great challenges that the latest pandemic (COVID-19) has imposed on manufacturing companies, the need to overcome and cope with such situations is becoming crucial. Supply chain resilience is one of the main aspects that enables manufacturers to cope with change and uncertainty; therefore, it is essential to develop the capabilities necessary to do so. This study aimed to ensure supply chain resilience in light of the COVID-19 pandemic through prioritizing main supply chain capabilities. After surveying (30) experts in supply chain from leading manufacturing companies in Jordan, a Fuzzy Analytic Hierarchy Process (FAHP) analysis was conducted to prioritize main supply chain capabilities that were derived from the related literature. The results of this study showed that proactive capabilities, followed by reactive capabilities, were the most dominant capabilities that could ensure supply chain resilience, while efficiency-based capabilities were the least significant. Therefore, manufacturing companies should place their focus and emphasis on reacting to this pandemic in a more systematic manner.

Selection of Wind Turbine Systems for the Sultanate of Oman

The Sultanate of Oman has been dealing with a severe renewable energy issue for the past few decades, and the government has struggled to find a solution. In addition, Oman’s strategy for converting power generation to sources of renewable energy includes a goal of 60 percent of national energy demands being met by renewables by 2040, including solar and wind turbines. Furthermore, the use of small-scale energy from wind devices has been on the rise in recent years. This upward trend is attributed to advancements in wind turbine technology, which have lowered the cost of energy from wind. To calculate the internal and external factors that affect the small-scale energy of wind technologies, the study used a fuzzy analytical hierarchy process technique for order of preference by similarity to an ideal solution. As a result, in the decision model, four criteria, seventeen sub-criteria, and three resources of renewable energy were calculated as options from the viewpoint of the Sultanate of Oman. This research is based on an examination of statistics on energy produced by wind turbines at various locations in the Sultanate of Oman. Further, six distinct miniature wind turbines were investigated for four different locations. The outcomes of this study indicate that the tiny wind turbine has a lot of potential in the Sultanate of Oman for applications such as homes, schools, college campuses, irrigation, greenhouses, communities, and small businesses. The government should also use renewable energy resources to help with the renewable energy issue and make sure that the country has enough renewable energy for its long-term growth.

Quantitative assessment of sustainable renewable energy through soft computing: Fuzzy AHP-TOPSIS method

Green energy resources need to be mobilized at an imminent pace to fulfill the world’s energy requirements that are both sustainable and cost-effective. Utilizing soft computing for generating sustainable power effectively eliminates additional requirements and costs. The selection procedure of Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preferences by Similarity to Ideal Solution (FTOPSIS) plays a focal part in sustainable power and soft computing. We assess and analyze to create a long-term renewable energy control system with enhanced system protection against cyber-attacks. The factors affecting the sustainable renewable energy resources selected in primary level further every initial factors have five dependent secondary factors are selected for the assessment. The different approaches of generation of renewable energy are taken as alternatives. FAHP technique is required due to the nature of the characteristics involved in evaluating the performance assessment of the renewable energy control system and the weight of the factors. The FTOPSIS-based technique looks to be a good strategy for selecting the best option from a large number of options. The finding shows that Wind energy is fully sustainable most preferable and leading renewable energy source. The proposed work’s novelty will stem from the use of hybrid soft computing techniques and the application of the issue to the energy industry.

Customisation of green buildings assessment tools based on climatic zoning and experts judgement using K-means clustering and fuzzy AHP

Utilising green building regulations and classifications by using well-known assessment tools such as LEED can be challenging in a country with various climates due mainly to specific sustainability priorities for each climate. This paper presents a new framework to customise assessment tools of green buildings for regions or countries with various climates. The framework comprises K -means method to cluster various climates of the region combined with the silhouette value (SV) for clustering verification and local experts' judgement for local customisation of green building assessment tools. The Fuzzy analytical hierarchy process (AHP) is used to adjust the regulations for each climatic zone. The proposed methodology is demonstrated by its application to the real-world case study of Iran. The K -means clustering with SV divides the country into four distinct climatic zones each representing with four meteorological parameters (MP, DTR, CDD, and HDD). Results show each climatic zone can take weights for sustainability categories and criteria based on its climate e.g. higher weight for “Water Efficiency” in zones with low rainfall and higher weight for “Energy and Atmosphere” in zones with heating or cooling needs. Results also show the two categories of “Energy and Atmosphere” and “Water Efficiency” take the largest weights in all zones by an average of almost 27 and 26%. These two categories, alongside with “Sustainable Site”, had the most changes in their weights for each climatic zone. The findings of this research reveal the effects of local climates on sustainability priorities of a green building assessment tool. • A new climate-based customisation of green building assessment tool is developed. • Sustainability categories and criteria are identified based on Delphi methodology. • K-means clustering technique and silhouette value are used to specify climatic zones. • Relevant experts are participated for climate assessment using Fuzzy AHP technique. • Findings reveal effects of climatic clustering on green building assessment tools.

Erbil Basin Groundwater Recharge Potential Zone Determination Using Fuzzy-Analytical Hierarchy Process (AHP) in North Iraq

Severe water scarcity has occurred in the Erbil Basin (EB) due to climate change and mismanagement of water resources during the past three decades. Assessment of the potential area of groundwater recharge is extremely significant for the protection and management of groundwater systems and water quality. This research aims to use the Fuzzy-Analytic Hierarchy Process (F-AHP) technique to recharge the aquifer in places in the EB that are likely to be groundwater recharge areas in a geographic information system (GIS) environment. GIS, remote sensing (RS), and F-AHP techniques were used to map the groundwater recharge potential zone in EB. Eight different geo-environmental factors were used to determine potential groundwater areas, namely: rainfall, lithology, geology, soil, slope, lineament density, land use/land cover (LULC), and drainage density (Dd). Then, the weights of the different thematic layers were assigned using a pairwise comparison matrix through the F-AHP. The total groundwater potential zone was shown to cover a very high area of 210.85 square kilometers (km2), a high area of 188.94 km2, a moderate area of 573.06 km2, a low area of 1956.48 km2, and a very low area of 216.34 km2, according to the groundwater recharge potential zones (GWRPZs) map. As a result, nearly one-third of the areas investigated were found to have moderate-to-very high groundwater recharge potential. This type of research can provide decision-makers and local governments with a broad perspective on current and future planning for groundwater scarcity.

Personalized Route Recommendation Using F-AHP-Express

The route recommendation system helps the driver find the best route between origin and destination. A recommendation system often suggests its decision without considering some criteria. This paper proposes a multicriteria decision-making method, namely Fuzzy—Analytic Hierarchy Process—Express (F-AHP-Express) for recommending a personal travel route from several alternative routes. It is calculated based on the driving preferences of a driver and road conditions for each road segment. We compare the F-AHP-Express to others; Fuzzy—Analytic Hierarchy Process (F-AHP) and Fuzzy—Analytic Hierarchy Process—Technique for Others Preference by Similarity to Ideal Solution (F-AHP-TOPSIS), for its recommendation results, time processing, agility, and complexity. Our experiments show that F-AHP-Express could deliver similar recommendation results compared to other methods, and it is additionally the fastest method. F-AHP-Express is 45% and 23% faster than F-AHP and F-AHP-TOPSIS, respectively. F-AHP-Express not only has the fastest time processing among the others but also has the least judgments in agility testing. It needs 37.5% and 16.67% fewer judgments from F-AHP and F-AHP-TOPSIS, respectively. Moreover, AHP-Express has a complexity of O(n), meanwhile, the others have O(n2) for their complexity. Thus, the results show that F-AHP-Express is the best method for recommending a personal route.

Trapezoidal interval type-2 fuzzy analytical hierarchy process technique for biophilic element/design selection in lodging industry

Recently, hoteliers focussed shifts on green practices because of sustainable goals. Also, guests are more health-conscious nowadays. Hence, biophilic elements and designs attract hoteliers and guests, and selecting the best biophilic elements/designs is one of the most important decision-making problems in the lodging industry. This study investigates the various biophilic elements/designs as main criteria and sub-criteria and evaluates them through the trapezoidal interval type-2 fuzzy analytic hierarchy process technique. Once the main biophilic elements and sub-biophilic elements for hotel selection are identified, the hierarchy structure has been designed. Then the weights are calculated using the interval type-2 fuzzy analytic hierarchy process technique. Finally, the biophilic element/design with the highest priority weight is selected as the most preferred by the guests. The robustness of the results is checked by comparing them with the results of the crisp analytic hierarchy process and sensitivity analysis. The findings of the study will help the decision-makers of the lodging industry in making more efficient and effective strategies.