Fuzzy Analytic Hierarchy Process Research Articles

Integrating fuzzy analytic hierarchy process into ecosystem service-based spatial planning: A case study of the Shenyang metropolitan area, China

Incorporating ecosystem services (ESs) into spatial planning is crucial for effective environmental management and achieving sustainable development goals. While the Analytic Hierarchy Process (AHP) is a commonly employed method for multicriteria analysis of ESs, it has faced criticism for its limited ability to handle inherent imprecision and uncertainties. Consequently, we proposed an assessment framework for ESs using the Fuzzy Analytic Hierarchy Process (FAHP) and implemented it in the Shenyang Metropolitan Area (SMA), a key political and economic center in Northeast China. We quantified eight types of ESs (water yield, food supply, water regulation, carbon storage, waste regulation, soil retention, habitat quality, and outdoor recreation) within SMA. The FAHP was utilized to determine the weights of these ESs. Subsequently, we presented a normalized index to identify priority conservation and development areas. Our results indicated that the primary areas for conservation were mainly located in the southwest and east of Benxi City, the southeast of Fushun City, and the southeast of Anshan City, whereas areas for development were primarily in the northwest of Shenyang City. Through comparing various ES integration methods, our study underscores the effectiveness of FAHP in ES evaluation. The research also highlights the challenge of managing uncertainties in ES-based policy-making and emphasizes the necessity for resilient and comprehensive planning approaches.

ANALISIS PEMILIHAN SUPPLIER KACA LEMBARAN DENGAN MENGGUNAKAN METODE FUZZY ANALYTICAL HIERARCHY PROCESS DAN TOPSIS

PT. XYZ is a company engaged in the automotive manufacturing sector since 1984, producing various kinds of car and motorcycle mirrors, electric door mirrors, auto lamps, lamp cases, and grilles. The majority of the company's customers are large-scale automotive companies, so they want excellent product quality. In improving product quality in terms of price, materials and services, this company requires the right supplier to continue to compete and maintain the company. The problem with the company requires a method for selecting priority suppliers so that the company can meet customer demands and increase its competitiveness. To solve these problems, researchers used the Fuzzy Analytical Hierarchy Process (FAHP) method and the Technique for Orders Preference by Similarity to Ideal Solution (TOPSIS) method. Supplier selection is carried out by considering 5 criteria, 10 sub-criteria, and 5 alternative suppliers. The results of the Fuzzy AHP calculation show that the first rank is SP2 with a weight of 0.392, followed by SP1 with a weight of 0.271, SP5 with a weight of 0.134, SP3 with a weight of 0.103, and finally SP4 with a weight of 0.100. Meanwhile, in the TOPSIS calculation, SP2 was obtained as the first rank with a weight of 0.847; followed by SP1 with a weight of 0.604, then SP4 with a weight of 0.506, SP5 with a weight of 0.488, and finally SP3 with a weight of 0.486. So the conclusion from this study is Supplier 2 (SP2) as the best alternative for the company to be prioritized in ordering flat glass raw materials based on the results of weight calculations using the FAHP and TOPSIS methods.

Reprocolla: Requirements Prioritisation Model with Collaboration Perspectives Based on Cost-Value Approach

The process of ranking requirements in software development is made up of various criteria and numerous stakeholders, which are properly selected for the effective prioritisation of software requirements. These requirements have encountered several challenges, including lack of scalability, complexity of pairwise comparisons and biases due to the cognitive load on stakeholders. Therefore, this research aimed to investigate and find solutions to improve the software prioritisation process using the Reprocolla model. The model was built by weighing the criteria in terms of benefits, opportunities, costs, and risks (BOCR) classification, which were then calculated using the fuzzy analytic hierarchy process (FAHP) method. Furthermore, the selection of alternatives was computed using the fuzzy technique for order preference using the similarity to an ideal solution (FTOPSIS) method. The success of Reprocolla was evaluated using seven datasets based on real projects and compared with the two existing methods for prioritising requirements, FAHP and FTOPSIS. The experiment results used inferential and descriptive statistics approaches with three indicators: accuracy, time consumption, and ease of use. Based on the three indicators mentioned above, the inferential statistics showed no significant difference between the perspectives of clients and developers. Whereas, descriptive statistics found that Reprocolla is more accurate, consumes less time, and has the highest ease of use percentage. The result showed that as stakeholders’ satisfaction level increases, the software development process becomes more accurate, thereby leading to a decrease in time consumption and a rise in ease ofusage. The result also showed that the development of the Reprocolla tool, a collaboration between humans and machines, enhanced the effectiveness of the requirements prioritisation process.

Examining the role of digitalization and technological innovation in promoting sustainable natural resource exploitation

In the era of technological advancement, the potential of digitalization and technical innovation to revolutionize sustainable resource exploitation has become a focal point. The promises of reduced environmental impact, heightened efficiency, and improved socio-economic outcomes underscore the transformative power that digitalization holds for resource management. To this extent, the fuzzy Analytical Hierarchy Process (AHP) and fuzzy VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) methods are used to examine challenges and come up with possible solutions for the mining sector in Pakistan to adopt digital transformation. The study identifies several key challenges, sub-challenges, and strategies, giving readers a thorough grasp of digital transformation. These challenges and sub-challenges are evaluated and ranked according to their relative weights using the fuzzy AHP approach. The fuzzy VIKOR method is applied to determine strategies that can help overcome these challenges and promote digitalization and technological innovation in the sustainable exploitation of natural resources. The results of fuzzy AHP show that policy and regulation, infrastructure, and human capital are key challenges. The findings of fuzzy VIKOR indicate that robust policy development, investment in Research and Development (R&D), and leveraging global trends and partnerships are key strategies to overcome the challenges. These findings provide valuable insights for policymakers, researchers, and practitioners, offering new perspectives on integrating digital technology into the natural resource sector to foster sustainable development.

Wind farm site selection using GIS-based mathematical modeling and fuzzy logic tools: a case study of Burundi

Introduction: The electricity generated from nuclear plants and petroleum-based products has a negative influence on the environment as a whole. It has shown the utility to search out and promote the utilization of renewable, environmentally friendly, and sustainable energy sources such as solar, wind, and geothermal. Nowadays, Wind energy resource has quickly emerged as the world’s fastest-growing energy source.Methods: However, the selection of the most suitable places for developing a wind farm is a crucial challenge that can be seen as a problem of site selection, which involves numerous conflicting variables. Therefore, it is classified as an MCDM (multi-criteria decision-making) problem. The main objective of this research is to determine the best locations in Burundi for the installation of wind farms. The Fuzzy Analytic Hierarchy Process (FAHP) was used to weigh the criteria considering their relative importance. This study considers several key factors when determining the optimal location for a wind farm. These factors include wind speed, slope, proximity to the grid network, distance to roads, and land use/land cover (LULC). Furthermore, a geographic information system (GIS) is utilized to generate the final suitability wind farm locations map.Results and Discussion: The obtained results indicate that 20.91% of the whole study area is suitable nevertheless, only 1.96% is tremendously suitable for wind turbine placement. The western part of Burundi is the optimal area for constructing a wind farm, and the most is in Lake Tanganyika.

Spherical Fuzzy Multicriteria Decision Making for Evaluating Healthcare Service Quality of Hospitals During the Global Pandemic

AbstractThis study identifies hospitals in Iran that have demonstrated exceptional performance in service quality during the COVID-19 pandemic based on the proposed integrated multicriteria decision-making (MCDM) process. Although the coronavirus has been eradicated in most countries, occasional outbreaks of COVID-19 variants have occurred, affecting many individuals, particularly in Iran. The pandemic caused an influx of hospital visits, with people seeking treatment for various illnesses. However, the abrupt onset of the pandemic and its global impact challenged hospitals’ ability to provide timely care, leading to a noticeable decline in service quality. Identifying the top-performing hospitals is crucial for benchmarking and enhancing healthcare quality. To assess hospital service quality, the study employed a customized SERVQUAL model, which helped identify key factors that served as criteria and subcriteria for the evaluation process. The priority weights of these factors were then obtained using the spherical fuzzy analytic hierarchy process. For each SERVQUAL criterion, the hospitals were evaluated using the spherical fuzzy weighted aggregated sum product assessment method, resulting in respective rankings of the hospitals. Finally, an integrated Borda−Copeland method was utilized to generate the aggregate evaluation ranking, a feature that serves as an important departure from the literature. The contribution of this work lies in developing an integrated approach that intends to serve as a benchmark not only for hospitals in different countries but also for those confronting similar challenges and offers guidance for seeking insights from top-performing hospitals in comparable situations.

A geospatial analysis of flood risk zones in Cyprus: insights from statistical and multi-criteria decision analysis methods.

Over the past few decades, flood disasters have emerged as the predominant natural hazard in Cyprus, primarily driven by the escalating influence of climate change in the Mediterranean region. In view of this, the objective of this study is to develop a geospatial flood risk map for the island of Cyprus by considering 14 flood hazard factors and five flood vulnerability factors, utilizing geographic information systems (GIS) and remotely sensed datasets. A comparative assessment was conducted for hazard mapping, employing statistical methods of frequency ratio (FR) and FR Shannon's entropy (FR-SE), and multi-criteria decision analysis method of fuzzy analytic hierarchy process (F-AHP). The main findings indicated that the FR method exhibited the highest predictive capability, establishing it as the most suitable approach for flood hazard mapping. Additionally, vulnerability factors were aggregated using F-AHP to generate the vulnerability map. The resulting flood risk map, which is the product of flood hazard and flood vulnerability, revealed that 9% of the island was located within highly risky regions, while 13.2% was classified as moderate risk zones. Spatial analysis of these high-risk areas indicated their concentration in the primary city districts of the island. Therefore, to mitigate future risks within these cities, an analysis of potential expansion zones was conducted, identifying the best-suited zone exhibiting the lowest risk. The generated flood risk map can serve as a valuable resource for decision-makers on the island, facilitating the integration of flood risk analysis into urban management plans.

Selection of waste receiving companies for sustainable industrial symbiosis network: an application a case in Ankara for foundry industry waste

AbstractIn the past twenty years, besides the technological and innovative efforts for production processes, there have been activities for the recovery and quality improvement of waste based on the development of sustainable solutions. These activities bring us closer to zero waste by protecting natural resources and reducing the environmental impact of production facilities. One of the essential approaches in this process is the industrial symbiosis (IS) approach. Efforts to implement the industrial symbiosis approach in an industrial park constitute the motivation of the study. The study aims to identify alternative enterprises that can evaluate the wastes generated in the main production process of the foundry industry with industrial symbiosis and rank them to establish a symbiotic relationship. First, the Pythagorean Fuzzy Analytical Hierarchy Process (PF-AHP) model has been developed to evaluate organizational factors, waste-specific factors, and economic and environmental sustainability criteria for establishing an IS network among alternative businesses. Then, alternative businesses were ranked to establish a symbiosis network with the PF-TOPSIS method. The proposed method contributes to the solution of a real-life problem that may arise when there are multiple alternatives to cooperate in the field of industrial symbiosis. By contributing this framework to the literature, the robustness of the results has been demonstrated through sensitivity analysis and comparative analysis. According to the results obtained, it was seen that the importance levels of economic factors came to the fore. Furthermore, among the alternatives, enterprises with high waste exchange potential, such as cement, took first place in the ranking.

Identifying and prioritization barriers to renewable energy diffusion in developing countries: a novel spherical fuzzy AHP approach and application

Identifying and prioritization barriers to renewable energy diffusion in developing countries: a novel spherical fuzzy AHP approach and application

An ideal location selection of electric vehicle charging stations: Employment of integrated analytical hierarchy process with geographical information system

Electric vehicle charging station identification is more essential in developing countries regions. Two major Middle Eastern capital cities are used to identify the EVCS which is important for environmentally friendly scenarios using the Analytical Hierarchy Process (AHP) and the Fuzzy-AHP (FAHP) in Baghdad (Iraq), and Riyadh (Saudi Arabia). With the help of GIS and multi-criteria decision analysis, suitable sites aimed at EVCSs are identified using twelve criteria. Based on the analysis very high suitable zones of Baghdad city have 179.99 km2 (AHP), and 162.61 km2 (FAHP), while Riyadh has 44.51 km2 (AHP), and 34.27 km2 (FAHP) respectively. Whereas, very low suitable areas for Baghdad have 552.47 km2 (AHP), and 1596.74 km2 (FAHP), while Riyadh has 518.43 km2 (AHP), and 463.59 km2 (FAHP) correspondingly. Karkh, Dora, Hurriya, Yarmouk, Binouk, and near the Baghdad international airport are more suitable for EVCSs establish while in Riyadh Dhahrat Laban, Ash Shifa, Al-Sina'yah, Tuwaiq, Al-Olaya and Al-Murabba is more Suitable for EVCSs. Green energy-based vehicle fuel is required for future development and reduction of fossil fuel use. Near the future, electric vehicles capture the maximum vehicle market, therefore identification of suitable sites for EVCSs plays a vital role in sustainable development.

Assessment of Green Supply Chain Management Practices Using Fuzzy Analytical Hierarchy Process

Assessment of Green Supply Chain Management Practices Using Fuzzy Analytical Hierarchy Process

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.

Prioritizing the valorization strategies of an invasive fern (Azolla) in a wetland

Wetlands play a vital role as one of the most important natural habitats on our planet. However, the survival of wetlands is threatened by various issues, including the arrival of invasive and non-native aquatic ferns. In this regard, Azolla filiculoides has become a serious problem for the Anzali wetland. The valorization of Azolla can contribute to the establishment of a collection system for this invasive fern, which can consequently reduce the harmful impact of this fern on the wetland, and it can be considered as a free and available source of biomass. Therefore, a fuzzy analytical hierarchy process was applied to rank the valorization strategies of this invasive fern. In the first step, four evaluation criteria (technical, economic, social, and environmental) and six valorization strategies were identified for the analysis through a literature review and expert opinions. The valorization strategies for Azolla were: 1) no collection, 2) collection and landfilling, 3) direct use as livestock and poultry feed, 4) composting, 5) biogas generation, and 6) biodiesel generation. The results revealed that the economic criterion had the highest priority for Azolla valorization, followed by environmental, technical, and social criteria, respectively. Regarding the valorization strategies, biodiesel was identified with the highest priority according to economic and social criteria, and biogas was the strategy with highest priority based on the environmental and technical criteria. In overall, biodiesel, biogas, and composting were ranked as the most appropriate valorization strategies for Azolla in the investigated wetland, respectively. Implementation of the identified valorization strategies can potentially promote the circular economy at the regional level and reduce the adverse effects of the invasive fern on the wetland ecosystem.

Bridging the knowledge gap of restaurant DINESERV attraction attributes between customer expectations and restaurateur priority ranking

ABSTRACT This study aims to explore and reveal the perception gap of restaurant attraction attributes between customers’ expectations and restaurateurs’ prioritization in casual and fine dining Korean table d’hôte restaurants. This study surveys the 16 critical restaurant attributes for restaurant visiting customers and restaurateurs. And, we employ the integrated importance-performance analysis (IPA) and fuzzy analytical hierarchy process (FAHP) approaches by setting the customers’ importance and the restaurateurs’ priority ranking for restaurant attributes as vertical and horizontal axes, respectively. The results of integrated IPA-FAHP suggested that most of the restaurant attributes were situated in the “Pairwise Harmonic Zone,” indicating that the customers’ importance and restaurateurs’ priorities were in agreement. Conversely, the attributes such as “restaurant ambience” and “restaurant sanitation and cleanliness” placed a relatively lower restaurateurs’ priority compared to high customers’ expectations. Casual and fine dining restaurants have different restaurant attraction attributes and operating strategies. Restaurateurs require operating initiatives and leverage strategies tailored to their characteristics to maximize operational efficiency. This study is a first attempt to bridge the perception gap of restaurant attraction attributes between expectation and priority ranking by using integrated IPA-FAHP approaches. We provide restaurant operating guidelines combining both customers’ and restaurateurs’ perspectives on restaurant attributes.

To Develop Ground Water Quality Index using Fuzzy AHP at Tamsa Watershed

To Develop Ground Water Quality Index using Fuzzy AHP at Tamsa Watershed

Assessment of Intelligent Unmanned Maintenance Construction for Asphalt Pavement Based on Fuzzy Comprehensive Evaluation and Analytical Hierarchy Process

Conventional human-involved maintenance methods for asphalt pavement pose significant challenges when applied to high-traffic road sections, often leading to congestion and safety risks, as well as reduced maintenance efficiency. In recent years, explorations into unmanned construction technology for newly constructed expressways have yielded beneficial and encouraging results. However, its application in road maintenance in more complex environments still needs to be expanded. In this study, an intelligent unmanned maintenance technology for asphalt pavement was applied to the Lilong Highway in Zhejiang Province, China, and the compactability, thickness, surface smoothness, permeability coefficient, and constructure depth of maintenance road sections were measured. Then, based on fuzzy comprehensive mathematics and the analytic hierarchy process, a comprehensive evaluation was performed on the intelligent unmanned maintenance technology, considering the aspects of road quality, safety, application, and socio-economic benefits. The results show that the road quality of intelligent unmanned maintenance technology can meet the road specification requirements. In addition, the membership degree of unmanned maintenance technology in the excellent grade is the highest, reaching 0.805, and the quantified value for the overall evaluation of the application effectiveness of unmanned maintenance technology is 92.10. This means that the final comprehensive evaluation result of unmanned maintenance technology is rated as excellent. The research findings provide decision-makers with valuable insights into the unmanned automation maintenance challenges faced by asphalt pavement, enabling them to implement appropriate measures to elevate the maintenance standards of road transportation.

Evaluation of factors impacting University-Industry collaboration by Fuzzy AHP and Fuzzy TOPSIS methods

University-industry collaboration (UIC) is viewed as a means to boost innovation through knowledge sharing. The purpose of this study is to investigate the importance ranking of factors influencing UIC and UIC models in the context of Vietnam. To begin, a systematic literature review (SLR) of previous academic studies on the subject of university-industry collaboration was conducted in order to identify the influential factors in UIC. The order ranking of factors and their relevance weights are then determined using the fuzzy AHP approach. The fuzzy TOPSIS is then used to evaluate three models for UIC, including collaboration in scientific research, technology transfer, and training. The results show that the number of scientists and experts and the awareness of the benefits of cooperation are the most important factors in implementing UIC; meanwhile, the experience of cooperation and training activities and student recruitment activities are evaluated less important than others. In addition, in the context of Vietnam, among UIC models, the technology transfer collaboration should be prioritized. Finally, based on the findings, discussions and policy implications are provided to promote UIC activities.

EWFAIGF: Design of an Efficient Model for Enhancing Energy Efficiency in IoT-Based Wireless Sensor Networks through Fuzzy AHP and Iterative Grey Wolf Jelly Fish Optimization

In the realm of Wireless Sensor Networks (WSNs), the quest for enhanced energy efficiency remains paramount, given their pivotal role in facilitating the Internet of Things (IoT) applications. Existing methodologies often grapple with the dual challenge of optimizing energy consumption while ensuring robust data transmission, thereby limiting their efficacy in dynamic, resource-constrained environments. This work introduces a novel paradigm that meticulously addresses these constraints, thereby heralding a significant leap towards optimizing WSNs' operational efficiency. At the core of our proposed model lies the integration of Fuzzy Analytic Hierarchy Process (Fuzzy AHP)-based clustering, which ingeniously segregates nodes by leveraging multi-criteria such as location, energy efficiency, and temporal performance. This clustering serves as a precursor to the application of an innovative Iterative Grey Wolf Jelly Fish Optimizer (GWJFO). The GWJFO stands out by its strategic prowess in delineating optimal routing paths, thus minimizing energy expenditure and enhancing data relay efficiency. Furthermore, our model is fortified with a Q Learning Method, ingeniously designed to identify and execute optimal alternate routing paths through a Make Before Break strategy. This addition not only mitigates potential faults but also significantly boosts computational efficiency and packet delivery performance. Empirical validation through real-time network simulations underscored the model's superiority, demonstrating a 9.5% improvement in communication speed, an 8.5% increase in energy efficiency, a 4.5% improvement in packet delivery performance under fault conditions, a 10.4% rise in throughput, and a 5.9% enhancement in network consistency over existing benchmarks. This groundbreaking work not only paves the way for more energy-efficient WSNs but also sets a new standard in achieving high-performance metrics essential for the next generation of IoT applications. The implications of these advancements extend beyond mere technical enhancements, offering a beacon for future research in the domain, potentially revolutionizing the way we deploy and manage sensor networks in an array of applications. 

Development of an Integrated Model for Open-Pit-Mine Discontinuous Haulage System Optimization

The selection of the optimal equipment for discontinuous haulage systems is one of the most important decisions that need to be made when an open-pit mine is designed. There are a number of influencing factors, including natural (geological and environmental), technical, economic, and social. Some of them can be expressed numerically, in certain units of measure, while others are descriptive and can be stated by linguistic variables depending on the circumstances of the project. These factors are characterized by a high level of uncertainty, associated with both exploration and mining operations. The experience, knowledge, and expert judgment of engineers and specialists are of key importance for the management of mining processes, consistent with the issues stemming from the dynamic expansion of open-pit mines in space over time. This paper proposes an integrated model that translates all the criteria that affect the selection of the optimal solution into linguistic variables. By employing the multiple-criteria decision-making method and combining it with fuzzy logic, we developed an algorithm that addresses all the above-mentioned uncertainties inherent in various mining processes where the experience of experts forms the basis. The fuzzy analytic hierarchy process is used in order to deal with trending decision problems, such as mining equipment and management system selection. The entire algorithm was applied to a real case study—the Ugljevik East 1 open-pit mine.

Construction of Product Appearance Kansei Evaluation Model Based on Online Reviews and FAHP: A Case Study of Household Portable Air Conditioners

Meeting the personalized needs of users is the key to achieving the sustainable success of a product. It depends not only on the product’s functionality but also on satisfying users’ emotional needs for the product’s appearance. Therefore, researchers have been conducting research focusing on Kansei engineering theory to determine users’ emotional needs effectively. The initial process involves accurately extracting and filtering emotional data and Kansei words from consumers. Thus, we propose an evaluation model to efficiently obtain, screen, and sort these Kansei words based on Kansei engineering, using household portable air conditioners as research subjects. By integrating techniques for online user comment mining methods, users’ Kansei terms related to the product’s appearance can be gathered efficiently. These terms are then combined with image samples and filtered to determine a final set of 16 Kansei word pairs. Subsequently, the fuzzy analytic hierarchy process (FAHP) is utilized to prioritize these terms, and the fuzzy comprehensive evaluation (FCE) method is used to validate the results and determine the applicability of the evaluation model. The results showed that Kansei words could be quickly and objectively acquired using existing text mining techniques on online reviews. Moreover, the weights of different Kansei terms of the product’s appearance in the consumer’s perception are accurately produced through the FAHP. This evaluation model marks a significant advancement in accurately obtaining users’ emotional data in Kansei engineering. It offers valuable guidance for designing products that meet users’ personalized needs, enhancing design efficiency and reducing resource wastage at the early stages of designing, and improving the sustainability development of Kansei engineering.