Fuzzy Analytic Hierarchy Process Method Research Articles

Integrating fuzzy-AHP and GIS for solid waste disposal site selection in Kenitra province, NW Morocco.

Selecting an optimal solid waste disposal site is one of the decisive waste management issues because unsuitable sites cause serious environmental and public health problems. In Kenitra province, northwest Morocco, sustainable disposal sites have become a major challenge due to rapid urbanization and population growth. In addition, the existing disposal sites are traditional and inappropriate. The objective of this study is to suggest potential suitable disposal sites using fuzzy logic and analytical hierarchy process (fuzzy-AHP) method integrated with geographic information system (GIS) techniques. For this purpose, thirteen factors affecting the selection process were involved. The results showed that 5% of the studied area is considered extremely suitable and scattered in the central-eastern parts, while 9% is considered almost unsuitable and distributed in the northern and southern parts. Thereafter, these results were validated using the area under the curve (AUC) of the receiver operating characteristics (ROC). The AUC found was 57.1%, which is a moderate prediction's accuracy because the existing sites used in the validation's process were randomly selected. These results can assist relevant authorities and stakeholders for setting new solid waste disposal sites in Kenitra province.

Evaluating Lecturer Performance in Vietnam: An Application of Fuzzy AHP and Fuzzy TOPSIS Methods

Higher education is regarded as being of paramount importance in Vietnam and as being essential to raising the level of the country's labor force and promoting economic progress. Evaluation of lecturers is one of the institution's activities and a crucial component of managing human resources in higher education institutions. How to evaluate faculty members' overall performance using a range of criteria is one of the key evaluation-related challenges. This study presents a method that uses fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to assess and rank the performance of lecturers. Specifically, the evaluation framework is developed by identifying criteria and sub-criteria based on a comprehensive review of existing literature. Following that, the fuzzy AHP approach is used to determine the weights of the criteria and sub-criteria using the pairwise comparisons. The Fuzzy TOPSIS approach is employed to assess and prioritize lecturers identified through expert evaluation. When applied in group decision-making, utilizing fuzzy AHP and fuzzy TOPSIS promotes agreement among decision-makers and diminishes uncertainty in decision-making processes. The utilization of the multiple criterion measurement approach can then be used to carry out the evaluation. The suggested framework is also demonstrated via a case study. The use of this framework can improve the evaluation's objectivity, accuracy, and scientific methodology. It is believed that this work will assist managers of higher education institutions improve their standards for educational quality.

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.

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.

Prioritization of noise abatement methods for controlling hospital noise pollution

Noise pollution in hospitals has increased over the last few years to a level that can threaten the health and productivity of staff and patient safety. There are many control measures to reduce hospital noise. However, there is still no consensus on the best measures. This study aims to prioritize the control measures for reducing hospital noise. The work is divided into three phases. The first phase identifies and categorizes noise sources in hospitals through a review of the state-of-the art literature using Scopus®, ProQuest, PubMed, Google Scholar, Embase,™ and Web of Science™. The second phase identifies possible strategies for reduction of hospital noise and the best criteria for their adoption using findings from the literature review and interviews with corresponding experts. The third phase uses Fuzzy Analytic Hierarchy Process (FAHP) method and the Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS) method to weigh the criteria and to prioritize the control measures. Based on the results, hospital noise sources were classified into four groups: outdoor noise sources (29.7%), noise produced by domestic facilities (20.8%), indoor noise from human activities (27.5%), and noise produced by diagnostic and treatment equipment (22%). The study further arrives at a set of 9 criteria and 22 alternatives ranked using FAHP and fuzzy TOPSIS. The criteria’s weights were determined using the FAHP method, with feasibility (0.175), effectiveness (0.143), and interference with staff activities (0.140) being the most important criteria. It was found that engineering controls such as substitution of noisy equipment (rank = 1), using acoustic enclosures (rank = 2), using double-glazed windows (rank = 2), and soundproofing walls, doors, and windows (rank = 3) have priority for reducing hospital noise.

Mapping of potential areas for aquifer recharge in arid regions using the IF model and the fuzzy AHP method: the case of southeastern Tunisia

Mapping of potential areas for aquifer recharge in arid regions using the IF model and the fuzzy AHP method: the case of southeastern Tunisia

Safety of agricultural machinery and tractor maintenance planning with fuzzy logic and MCDM for agricultural productivity

Productivity is one of the most important measures used to determine the growth and development level of countries or sectors. A wide variety of projects have been planned and implemented to increase agricultural productivity. The productivity to be obtained in agriculture; Soil conditions, climate, seeds, fertilizer, pesticides, labor and agricultural mechanization directly affect it. Agricultural mechanization is the realization of agricultural activities by using energy together with agricultural tools and machines. Agricultural mechanization; It is an important agricultural production technology that helps increase agricultural productivity. Due to the inadequate maintenance planning of agricultural machinery, agricultural machinery cannot be utilized at the desired level in agricultural production. Most agricultural equipment is subject to frequent changes in speed and direction of movement while operating. Damage that can be seen on a single machine; It also causes other machines to malfunction. During the year, especially in the months when agricultural activity is high, excessive working tempo can cause tractors to malfunction. The breakdown of tractors causes disruptions in agricultural activities. In addition, the breakdown of tractors increases the repair costs. Since there is no tractor maintenance planning, farmers face interruptions in agricultural activities due to tractor malfunction. However, tractor malfunctions may cause cost and economic losses. For these reasons, there is a need for appropriate maintenance planning of agricultural machinery in order to continue agricultural activities without disruption. Maintenance planning; It consists of a set of preventive activities to improve the reliability and availability of any system. The main purpose of this study is to determine and rank the importance level weights of the criteria that are important for agricultural machinery maintenance planning using the fuzzy AHP method. Fuzzy AHP method, which provides ease of application, was preferred in determining the Criterion Weights. The research proposes a framework to determine the weights of appropriate criteria for care planning selection through a combined approach of fuzzy multi-criteria decision making involving relevant stakeholders. On the basis of the prioritization of criteria of tractor maintenance planning (TMP), it was found from the ranking that checking for all fluid levels (TMP1) ranked first. This respectively is followed by checking for general conditions (TMP4), checking for tires and wheels (TMP2) and checking for batteries (TMP3). With the results of the study, a guide was created for farmers and other stakeholders, as well as decision makers, to help plan the maintenance of machines in better working conditions. It is also thought that this study will be encouraging for other studies.

Analyzing the relationship between natural resource management, environmental protection, and agricultural economics for sustainable development in China

Sustainable development is crucial for achieving a balance between economic growth, social well-being, and environmental preservation. This study aims to evaluate the dimensions of natural resource management, environmental protection, and agricultural economics for promoting sustainable development in China. In this regard, the fuzzy Analytical Hierarchy Process (AHP) and fuzzy VIekriterijumsko KOmpromisno Rangiranje (VIKOR) approaches are used for the analysis. The hybrid approach combines the benefits of fuzzy logic and multi-criteria decision-making (MCDM) techniques, allowing for the consideration of uncertainties and imprecise data in decision-making. The study incorporates six criteria, twenty-four sub-criteria, and five strategies in a comprehensive evaluation framework. According to the results obtained using the fuzzy AHP method, it is evident that the primary criteria influencing sustainable development in China are economic viability, policy and governance, and environmental impact. Within these criteria, specific sub-criteria such as cost-effectiveness, policy alignment, air quality, and social inclusion emerge as key areas of focus. Furthermore, the results of the fuzzy VIKOR method show that investing in research and innovation, strengthening environmental regulations, and strengthening climate change adaptation are the most suited strategies to guide sustainable development efforts. To ensure sustainable development in China, policymakers need to give importance to implementing strategies stressing research and innovation, strengthened environmental regulations, and enhanced climate change adaptation.

APPLICATION OF PFAHP-GTOPSIS METHODS FOR THIRD-PARTY LOGISTICS PROVIDER SELECTION

Companies are now considering the option of outsourcing as hedges cost and increase productivity by concentrating on their core skills to update their supply chains due to the competition in global markets, the use of higher-quality products, and rising customer demands. They must carefully select and identify which company to collaborate with before outsourcing their numerous logistics-related tasks to Third-Party Logistics Providers (3PLP). However, the existence of uncertainties and human influence in 3PLP selection problems leads to the usage of fuzzy or related set theories. By incorporating Multi-Criteria Decision Making (MCDM) methods with fuzzy numbers and grey numbers, practical tools can be composed to address the imprecision of subjective judgments. From this perspective, an integrated MCDM model is proposed to provide insight into the 3PLP evaluation and selection. The model comprises an integrated framework with Pythagorean fuzzy numbers and grey numbers. The proposed model has applied a 3PLP a company in the food industry to fulfill customer orders. The evaluation criteria weights are calculated using the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) method, and the 3PLPs are ranked using the grey Technique for Order Preference by Similarity to Ideal Solution (GTOPSIS) methods to find the best 3PLP. The analyses and findings concluded that cost, service quality, and on-time delivery were the three criteria that had the greatest influence

Storm surge risk assessment and sensitivity analysis based on multiple criteria decision-making methods: a case study of Huizhou City

Coastal areas face escalating storm surge disasters due to rising sea levels and urban growth, posing greater risks to lives and property. Comprehensive storm surge risk assessment and sensitivity analysis in coastal areas are crucial for effective disaster prevention and mitigation. This research focuses on Huizhou, China, conducting a comparative study of storm surge risk assessment and sensitivity analysis based on an integrated approach, which includes the storm surge inundation numerical model (FVCOM-SWAN), Geographic Information System (GIS) and Remote Sensing (RS) techniques, and Multiple Criteria Decision-Making (MCDM) methods. Ten flood-related risk indicators are selected from the hazard, exposure and vulnerability, the weights of which are evaluated through a comprehensive comparison among Analytic Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), Entropy Weight (EW), AHP-EW, and FAHP-EW methods. High-precision risk level maps are generated subsequently utilizing GIS and RS techniques. Sensitivities of the indicators are analyzed using One-At-A-Time (OAT) and Fourier Amplitude Sensitivity Test (FAST) methods. The proposed storm surge risk assessment framework, the MCDM comparative study and the sensitivity analysis can offer insights for better understanding and management of storm surge risks, and contribute to the standardization and application of storm surge risk assessment.

Developing a Multi-Criteria Decision-Making model for nuclear power plant location selection using Fuzzy Analytic Hierarchy Process and Fuzzy VIKOR methods focused on socio-economic factors

In response to its position as the fourth most populous country globally, Indonesia is exploring constructing nuclear power plants (NPPs) as a sustainable energy solution. A pivotal step in this initiative is selecting an appropriate NPP site. This study employs two Multi-Criteria Decision-Making (MCDM) methods, the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy VIKOR, to identify the most suitable location for an NPP, focusing on socio-economic factors. The Fuzzy-AHP method is utilized to prioritize ten sub-criteria: transmission network, operating costs, economic impact, security, transportation network, legal considerations, the impact of tourism, land ownership, historical sites, and public acceptance. Following this, the Fuzzy VIKOR method leverages these prioritized criteria to evaluate two potential sites: East Kalimantan and West Kalimantan. The analysis reveals that security, transmission, and transportation networks emerge as the top priorities. The application of the Fuzzy VIKOR algorithm identifies West Kalimantan as the optimal site for NPP construction, evidenced by its lower VIKOR index of 0.3599, indicating a higher overall preference based on the evaluated criteria. The study demonstrates that the integration of Fuzzy-AHP and Fuzzy VIKOR methods prioritizes critical socio-economic factors and quantitatively assesses potential sites, offering a systematic and objective approach to support decision-making in NPP site selection.

Forecasting groundwater fluctuations caused by earthquakes using fuzzy logic and AHP Method: A case study from Iran

Forecasting groundwater fluctuations caused by earthquakes using fuzzy logic and AHP Method: A case study from Iran

VOC source apportionment, reactivity, secondary transformations, and their prioritization using fuzzy-AHP method in a coal-mining city in India.

This study assessed the air quality status in different functional zones of Dhanbad-a coal-mining and industrial hub, based on the measurement of aromatic and halogenated volatile organic compounds (VOCs) using gas chromatography. The study encompasses source apportionment of VOCs and their chemical reactivity in terms of OH radical loss rate (LOH), ozone-forming potential (OFP), and their secondary organic aerosol forming potential (SOAp). Furthermore, prioritization of VOCs based on a fuzzy-analytical hierarchical process (F-AHP) has also been done. The results found xylene species to have the highest concentration in all three seasons across traffic-intersection and industrial zones and toluene at the institutional zone. The study identified four sources using positive matrix factorization (PMF) model, viz., mixed traffic exhaust (35%), coal combustion sources (30%), industrial (26%), and solvent usage (9%). LOH and SOAp were ~ 16 times more at the industrial and traffic-intersection zone than the institutional zone. The aromatic species contributed 97% to the OFP, and many species exhibited less contribution to the mixing ratio of VOCs but displayed a high contribution to LOH, OFP, and SOAp, suggesting the need to prefer reactivity-based strategies in addition to concentration-based strategies in the future for their regulation. The F-AHP-based priority component analysis identified 16 species out of 29 in the priority watch list (nine in tier-1, four in tier-2, and three in tier-3). The paucity of data and lack of ambient air quality standards on VOCs (except benzene) make it difficult to determine which aspect should be dealt with first and which species require more attention. Therefore, the F-AHP method used in this study could help identify the influencing parameters to be considered while devising efficient VOC management policies.

Analisis Pemilihan Supplier Bahan Baku Tas Gitar dengan Metode Fuzzy Analytical Hierarchy Process (FAHP) di PT. True Indonesia

The use of high-quality raw materials will affect the quality of products produced by a company. Companies really need suppliers who can supply quality raw materials. This can be realized by selecting the most appropriate supplier so that the company can minimize problems that can occur regarding raw material suppliers. PT True Indonesia is a manufacturing company that produces music equipment bags. So far, the company has made decisions in choosing suppliers only with the intuition of the parts related to the procurement of these raw materials. The decision chosen by the company in determining this supplier is often not right. The problems experienced by the company are the quality of raw materials that do not meet the company's criteria and the supplier's delay in sending raw material orders. In this study, the Fuzzy Analytical Hierarchy Process (FAHP) method was used. There are 7 main criteria in choosing a polyester fabric supplier, namely quality, delivery, price, communication system, warranties and claim policies, performance history, and geographic location. From the calculations carried out, the best polyester fabric supplier ranking for PT True Indonesia in order, Tongxiang has a total value of 0,3395, Hantron has a total value of 0,3350, PT. Lambang Jaya has a total value of 0,3340, PT. Shinta Indah Jaya has a total value of 0,3174, and CV. Agung has a total value of 0.3116.

Comprehensive Performance Evaluation of an Unmanned Excavator Based on Signal Stability Extraction

The comprehensive performance of unmanned excavators is crucial for the development and optimization of the field of construction machinery. To effectively improve the unmanned excavator to meet the needs of the market, it is imperative to quantify the evaluation method of the comprehensive performance of unmanned excavators. In this study, an evaluation method combining a fuzzy analytic hierarchy process and multivariate image area analysis method is proposed. Firstly, based on the feature extraction of the signal stability of the unmanned excavators, fifteen evaluation indexes were proposed. Then, the case study is used to obtain the scores corresponding to these indexes. The fuzzy analytic hierarchy process is applied to determine the relative weight of the selected evaluation criteria, in which the uncertain and imprecise judgments of decision makers are converted into fuzzy numbers. At the same time, the braking performance of the three types of unmanned excavators was comprehensively evaluated and ranked using the multivariate image area analysis method as an empirical example. Finally, a weight analysis is performed to check the robustness of the ranking results. The results show that the proposed method is effective and feasible. It provides a reference for the performance improvement and efficiency optimization of unmanned excavators.

Research on Condition Assessment Method of Transformer Based on Cloud Model

The traditional evaluation method of transformer has the problems of strong subjectivity of threshold value and fuzzy correlation of state quantity, which is difficult to accurately evaluate the operation quality of transformer. In order to solve these problems, this paper proposes a comprehensive evaluation method of transformer performance evaluation and operation quality based on cloud model. The evaluation index system of power transformer operation quality considering performance is constructed, including target layer, performance layer and index layer. The triangular fuzzy number is used to optimize the set of expert opinions, and the indexes are combined and weighted by fuzzy analytic hierarchy process and entropy weight method. After the data is degraded, the membership matrix of transformer operation index is constructed by using the cloud model, and the performance state weighting and membership degree are comprehensively considered to realize the performance evaluation of transformer and the comprehensive evaluation of operation quality based on performance. By using this method to predict 10 transformers in operation for a period of one month, it is possible to accurately identify abnormal situations on site, with a prediction accuracy of 96.28%. Compared with the traditional method of “predicting first and then diagnosing”, it has improved by 14.32%, overcoming the shortcomings of subjectivity, ambiguity, and ignoring the correlation of state variables in traditional evaluation methods. This method provides new ideas and methods for accurate evaluation of transformers.

Identifying and ranking of the main organizational resilience indicators in the hospital during the COVID-19 pandemic: A study using fuzzy Delphi technique (FDT) and fuzzy analytical hierarchy process (FAHP)

Resilience in a hospital is referred to as the capability to withstand and respond to disasters while maintaining critical functions. The current study aims to identify and prioritize the defining indicators of organizational resilience in dealing with the critical conditions of the COVID-19 pandemic. First, a literature review and semi-structured interviews with experts were performed for the identification of the primary indicators affecting the hospital's organizational resilience in critical conditions caused by the COVID-19 disease. Next, the fuzzy Delphi technique (FDT) was used to determine the effective and final indicators with a 70% agreement level. Finally, the indicators were weighted and prioritized using the FAHP method. The results shows that three indicators of leadership and management (NW = 0.092), preparedness (NW = 0.080), and learning from previous experiences (NW = 0.078) had the greatest impact on the organizational resilience of the hospital, respectively. Three indicators of logistics support, fallibility culture, creativity, and innovation with the final weights of 0.56, 0.054, and 0.053 gained the least importance, respectively. It can be concluded that a higher level of leadership and management, preparedness, and learning from previous experiences in the conditions of the COVID-19 pandemic can help control this crisis.

Analisis Manajemen Rantai Pasok dengan Metode Supply Chain Operation Reference PT Fourmi Asha Sejahtera

In an era of economic development, business competition demands the acquisition of as many consumers as possible. This naturally requires a sound strategy in order to gain a competitive edge over rivals. The purpose this study evaluate performance of Multi-level Marketing (MLM) company’s supply chain with the SCOR model, which is one of the essential strategies a company should possess. This study uses the hybrid Best worst method (BWM) and Interval-valued Pythagorean Fuzzy Analytical Hierarchy Process (AHP) method to determine the highest-weighted criteria, this research seeks to identify performance metrics that need improvement. The data were collected by filling in tables, there are three groups of experts who participate in determining the highest-weighted criteria.  The results show metric Reliability are significant at the Level 1 with important weight of 0.36, and at level 3 the most significant metric for the multi-level marketing’s supply chain is Source with an important weight of 0.36.