Fuzzy Analytic Hierarchy Process Approach Research Articles

Exploring Internet of Things adoption challenges in manufacturing firms: A Delphi Fuzzy Analytical Hierarchy Process approach.

Innovation is key to gaining a sustainable edge in an increasingly competitive global manufacturing landscape. For Bangladesh's manufacturing sector to survive and thrive in today's cutthroat business environment, adopting transformative technologies such as the Internet of Things (IoT) is not a luxury but a necessity. This article tackles the formidable task of identifying and comprehensively evaluating the impediments to IoT adoption in the Bangladeshi manufacturing industry. We delve deeply into the complex terrain of IoT adoption challenges by synthesizing expert insights and a meticulously selected body of contemporary literature. We employ a robust methodology combining the Delphi method with the fuzzy Analytical Hierarchy Process to systematically analyze and prioritize these challenges. Using this methodology, we leveraged the combined expertise of domain specialists and subsequently employed fuzzy logic techniques to address the inherent ambiguities and uncertainties within the data. Our findings highlight this clear path. They reveal that among the myriad barriers, "Lack of top management commitment to implementing new technology" (B10), "High initial implementation investment costs" (B9), and "Risks associated with switching to a new business model" (B7) loom most extensive, demanding immediate attention. These insights are not confined to academia but serve as a pragmatic guide for industrial managers. Armed with the knowledge gleaned from this study, managers can craft tailored strategies, set well-informed priorities, and embark on a transformational journey toward harnessing the vast potential of IoT in the Bangladeshi industrial sector. This article provides a comprehensive understanding of IoT adoption challenges and industry leaders with the tools necessary to navigate these challenges effectively. This strategic navigation, in turn, contributes significantly to enhancing the competitiveness and sustainability of Bangladeshi manufacturing in the IoT era.

Evaluation of sustainable hydrogen production technologies by fuzzy AHP analysis with bootstrapping

The concept of a hydrogen economy has received increasing attention worldwide. Hydrogen is a promising energy carrier that contributes to the development of a sustainable and reliable energy sector. Selection of the most sustainable hydrogen production technology (HPT) plays a significant role in promoting a hydrogen economy. However, it is regarded as a multi-criteria decision-making (MCDM) problem with several incompatible evaluation criteria. In this study, we develop an MCDM approach based on Fuzzy Analytic Hierarchy Process (FAHP) for prioritizing HPT alternatives, focusing on Egypt as a case study. Our contributions are twofold. First, to combat the issue of a small number of subject matter experts, a bootstrap method is employed to validate the main criteria weights in FAHP. Second, we conduct a comparative FAHP analysis from a broad perspective of the national experts from a developing country and the international experts from developed countries. Our results show that PV electrolysis is the most preferable technology option from the perspectives of both the national and international experts. Since the FAHP approach proposed is a flexible framework that can be applied to countries other than Egypt, it will support global policymakers and industry stakeholders in their decision making toward a sustainable and efficient hydrogen economy strategy.

Identifying key safety investments needed for arctic shipping via a fuzzy analytic hierarchy process (FAHP) approach

ABSTRACT The retreating ice coverage and reduced (ice) thickness scientifically recorded in the wider Arctic region, during the last few decades, are transforming it into a more accessible operating environment. Vessels engaged in maritime transport activities can now navigate the already established routes for more extended periods each year. With this background, Arctic shipping routes have attracted the interest of academics and maritime stakeholders because of the potential distance reduction compared to other existing (and often viewed as) conventional routes utilizing the Suez and Panama Canals today. However, the existing Arctic shipping environment requires specific future safety investments. This paper intends to provide input towards better-informed decision-making and identification of priority investments needed to improve the level of safety related to the Northern Sea Route (NSR) and Northwest Passage (NWP). A multi-attribute decision-making methodology, the Fuzzy Analytic Hierarchy Process, is applied to rank the various proposed safety investments. The results indicate that “infrastructure and facility” should come first, followed by “personnel,” “technology,” “measure,” and “management” investments. Ice monitoring and weather forecasting, strengthening Arctic seafaring expertise, and icebreakers stand out as the top three most important future investments required in the region.

Managing uncertainties in urban junction design: a case study of the FAHP method in Chettia

The essay delves into how an urban crossroads in Chettia, Algeria was reconstructed using the Fuzzy Analytic Hierarchy Process (FAHP) method to assess and choose the best design from multiple alternatives. The inherent uncertainties in this type of project can be effectively managed by using fuzzy algorithms, which mimic human reasoning in decision-making. A comprehensive and organised study is made possible by the methodology's foundational premise on a hierarchical problem classification into 32 criteria and sub-criteria. To establish the weightings of these criteria and lay the groundwork for comparing alternatives, the FAHP approach is employed, which is well-known in the area of multi-criteria decision-making. The feasibility and efficacy of this method are illustrated in the case study pertaining to the reconstruction of the Chettia intersection. A global performance indicator was used to rate the four solutions that the experts reviewed. When it comes to building and maintaining rural road networks, this strategy is invaluable for making educated decisions. In this case, the FAHP method provides a rigorous and methodical way to choose the optimal design. It enables the management of the uncertainties inherent in this type of urban infrastructure project while considering various complicated and sometimes contradicting aspects. Urban planners and transportation engineers may benefit much from this concept if it were applied to other comparable projects.

Selection of data analytic techniques by using fuzzy AHP TOPSIS from a healthcare perspective

The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with different Data Analytic (DA) and machine learning algorithm approaches. Researchers, scientists, and industrialists must manage or select the best approach associated with DA in healthcare. This scientific study is based on decision analysis between the DA factors and alternatives. The information affects the whole system in a rational manner. This information is very important in healthcare sector for appropriate prediction and analysis. The evaluation discusses its benefits and presents an analytic framework. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach is used to address the weight of the factors. The Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) address the rank of the data analytic alternatives used in healthcare sector. The models used in the article briefly discuss the challenges of DA and approaches to address those challenges. The assorted factors of DA are capture, cleaning, storage, security, stewardship, reporting, visualization, updating, sharing, and querying. The DA alternatives include descriptive, diagnostic, predictive, prescriptive, discovery, regression, cohort and inferential analyses. The most influential factors of the DA and the most suitable approach for the DA are evaluated. The ‘cleaning’ factor has the highest weight, and ‘updating’ is achieved at least by the Fuzzy-AHP approach. The regression approach of data analysis had the highest rank, and the diagnostic analysis had the lowest rank. Decision analyses are necessary for data scientists and medical providers to predict diseases appropriately in the healthcare domain. This analysis also revealed the cost benefits to hospitals.

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.

Assessing collaboration performance of NGOs by a decomposed Fuzzy approach utilizing AHP and COPRAS methods: Turkiye case

With the increase in disasters that cause the loss of life and property of countless people in recent years, it has become essential for non-governmental organizations (NGOs) to work collaboratively and evaluate their performances. In order to assess the effectiveness of NGOs' collaboration in disaster management, the SERVQUAL model, which measures service quality and has applications in numerous fields, has been updated to reflect the demands of the modern age. The sub-criteria under the five main criteria have also been updated. This study makes use of Decomposed Fuzzy (DF) approaches, which may mitigate the language scale ambiguities that experts have when making decisions. While the criteria weights are found by the Decomposed Fuzzy Analytical Hierarchy Process (DF-AHP) approach, the alternatives are evaluated using the DF-COPRAS method, which combines the DF approach with the COPRAS method for the first time in the literature. The proposed novel model is employed to evaluate the collaboration performance of NGOs in disaster management in Turkiye. Sensitivity analysis and comparative analysis are presented as supplementary analyses of the study.

Application of decision support system/remote sensing/GIS techniques in groundwater recharge assessment

ABSTRACT Managing water resources and storing water through the identification of groundwater recharge zones (GWRZs) are critical to water security in Egypt. Decision-support systems (DSSs), remote sensing, and GIS techniques have yielded significant data for water resources modeling. The geologic, geomorphic, climatic, and hydrologic features of the Toshka area, Western Lake Nasser, Egypt, have been generated by data from Shuttle Radar Topography Mission, Climatic Research Unit gridded Time Series, Sentinel 2 time series, and Landsat-8 OLI. Fifteen GIS thematic maps have been ranked and normalized using five DSS techniques: Analytical Hierarchy Process (AHP), Fuzzy Analytical Hierarchy process (FAHP), Frequency Ratio (FR), Shannon Entropy (SE), and Multi-Influencing Factor (MIF). To ensure the computational usefulness of these models, GWRZs have been extracted and compared. The outcomes showed that 83, 87.5, 99.1, 99.1, and 87.5% of the existing wells are in high to extreme GWRZs for AHP, FAHP, FR, SE, and MIF, respectively. The receiver operating characteristic curve (ROC) was used to assess the effectiveness of these models. It was found that the SE model had the highest predictive performance rates, as its ROC accuracy value was 91.1%, while the FR, AHP, FAHP, and MIF approaches had values of 91, 84.4, 81.9, and 89.9%, respectively.

Hazard Identification and Risk Assessment for Sustainable Shipyard Floating Dock Operations: An Integrated Spherical Fuzzy Analytical Hierarchy Process and Fuzzy CoCoSo Approach

Background: This study investigated the process of selecting sustainable safety protocols for floating dock operations in shipyards by identifying potential workplace risks in emergency situations. Thirteen occupational hazards for shipyard floating dock operations were identified through a literature review and expert discussions. Methods: We incorporated four risk elements (consequence: C, frequency: F, probability: P, and number of people at risk: NP) from the Fine–Kinney and Hazard Rating Number System (HRNS) approaches as the risk assessment criteria. We obtained the importance weights of the risk assessment criteria via the Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) and extended the Combined Compromise Solution (CoCoSo) method within the fuzzy framework to prioritize occupational hazards. This study demonstrated the practicality and efficiency of the proposed emergency risk assessment model for shipyard floating dock operations through a case example of occupational risk assessment. Results: The analysis results show that H4 is the occupational hazard with the highest priority, with a score of 3.553. H4 represents the hazard associated with insufficient access to the entire pool area. The second and third most important hazards are the inability of cranes to move freely in and out of the berthing dock and the inability to dispatch emergency teams. These hazards, denoted H1 and H12, follow closely behind with scores of 3.391 and 3.344, respectively. H10 is deemed the least concerning hazard, with a score of 1.802. Conclusions: Professionals can handle complex and uncertain risk assessment data more flexibly using the proposed system, which excels in accurately organizing occupational hazards.

Assessing the relevance of an Indian undergraduate civil engineering programme: a fuzzy analytical hierarchy process approach

Assessing the relevance of an Indian undergraduate civil engineering programme: a fuzzy analytical hierarchy process approach

Using fuzzy analytical hierarchy process for road transportation services management based on remote sensing and GIS technology

Abstract The importance of site selection for road transportation management and emergency services has been underscored, particularly in the wake of the global Covid-19 pandemic in addition to road accident injuries, which emphasized the need for swift patient, injured and wounded peoples transfer to hospitals. As a result, comprehensive road transportation management is essential during crises to ensure the safety and convenience of road users. To achieve effective road network management, a robust database is imperative. The aim of this study is to employ multi-criteria decision analysis with the aid of Geographical Information System (GIS) technology and remote sensing for the optimization of site selection for traffic signals, fire stations, and emergency services in Kafr El-Sheikh city, Egypt. The methodology incorporates two different methods which are Fuzzy Analytical Hierarchy Process (F-AHP) and the spline transformation method. The integration of Fuzzy set theory with AHP principles has given rise to a variant of AHP known as F-AHP. F-AHP combines qualitative and quantitative approaches. Fuzzy logic handles situations that are vague or poorly defined by assigning numerical values. Through the F-AHP approach, criteria that decision-makers unanimously deem “absolutely not important” in comparison to others are eliminated, allowing them to focus on the most significant criteria. As a case study, an Egyptian city was selected to apply these techniques. The results revealed multiple sites that were identified and selected through the applied analytical methods. These selected sites were also marked on the city map and verified in reality.

Analytic Hierarchy Process to Choose the Best Sector in the Software Industry for a New Software Engineer

Objectives: To determine the best area in the software industry for a fresh engineering graduate in India. Methods: Examined the current situation of the software industry today and the datasets that were gathered and included in accordance with that. Here, five alternatives (Research and Development, Mobile solutions, Cloud computing, Big data analytics, and Government and Defence) and seven parameters (Communication, Teamwork, Coding and technical literacy, Programming languages, Problem-solving skills, Research skills, and Multitasking skills) are taken into consideration. Fuzzy AHP and fuzzy TOPSIS methods were used, and the outcomes were compared to the AHP method. Findings: Fuzzy AHP and fuzzy TOPSIS methods have been used to produce the normalized weight vector for each alternative relative to the criterion. Additionally, a normalized weight vector has been calculated and compared to every criterion and criteria alternative. Final rankings for each alternative have been determined in relation to all of these. Novelty: The novelty of the present study is to identify the best sector of the software industry in India for a recent engineering graduate based on providing a ranking of alternatives using fuzzy TOPSIS and fuzzy AHP methodologies. While other strategies may be used to do similar works, the techniques listed above may not be used. Fuzzy AHP and fuzzy TOPSIS approaches can provide more optimal solutions, which is an innovative aspect of this study. Keywords: Analytical Hierarchy Process (AHP), Comparative analysis, Fuzzy AHP method, Fuzzy TOPSIS method, Software industry

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.

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.

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.

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.

Identification and Weighting of Supply Chain Risks with the Help of Fuzzy Analytical Hierarchy Process Approach (Case Study: Mobarakeh Steel Complex of Isfahan)

Identification and Weighting of Supply Chain Risks with the Help of Fuzzy Analytical Hierarchy Process Approach (Case Study: Mobarakeh Steel Complex of Isfahan)

Supply Chain Resiliency in Post- COVID-19 Times: Evaluating the Inhibitors Using a Fuzzy Analytic Hierarchy Process Approach

The COVID-19 pandemic has significantly affected the way supply chains function and operate. Supply chain resiliency (SCR) has become increasingly more relevant to the pandemic, with corporations and governments realising that their supply chains were not as resilient leading to shortages/delays of many consumer products. Delays in the delivery of essential items, including medicines, food supplies and healthcare equipment, have exposed the challenges that a supply chain might face during a major disruption such as the global pandemic, regional conflicts and natural disasters. The purpose of this study is to identify and evaluate some of the critical inhibitors associated with SCR during COVID-19. The study employs multi-criteria decision-making utilising the fuzzy analytical hierarchy process. This research was conducted in the context of the Indian pharmaceutical supply chains. The research showed that there are seven major inhibitors to SCR. The findings of the current study are expected to aid the pharmaceutical supply chain managers in identifying and evaluating the critical inhibitors to achieving SCR and designing strategies to mitigate any future catastrophe like a global pandemic.

Towards an IoT based secured framework for smart cities

<p>Cities are evolving into smart urban environments, where various devices, technologies, services, connections, blocks, and storage systems are transforming to embrace smart solutions, departing from traditional counterparts. This intricate network of interconnected devices collectively constitutes the Internet of Things (IoT), promising users a life of enhanced convenience. However, this transformation also introduces challenges, particularly in managing loosely linked devices and transmitting information across networks. This study conducts a comprehensive review of the various components contributing to the formation of a smart city, scrutinizing the challenges and factors that influence them. The overarching objective is to identify specific areas within smart cities grappling with cybersecurity challenges and ascertain the relative significance of each area. Data for this research is gathered through questionnaires, expert opinions, and paired comparisons drawn from previous studies, and employs the Fuzzy Analytic Hierarchy Process approach to determine the weight of each factor and sub-factor, subsequently ranking them. Among the nine identified factors, the "Smart Security" factor is the most critical, with a weight of 0.198, signifying its paramount importance. To overcome the security challenges in smart cities, we introduce an advanced secure framework (ARPL) for detecting security threats, using the Routing Protocol for Low Power and Lossy Networks (RPL) as its foundation. The advanced framework is adept at identifying a variety of attacks. Performance assessments of the proposed framework encompass several key parameters, such as ADA, TPR, FPR, and end-to-end delay. The positive outcomes observed strongly endorse the effectiveness of the proposed framework, positioning it as an optimal solution for RPL-based smart environments.</p>

Determinants of employee engagement in the hotel industry: An application of fuzzy analytic hierarchy process approach

The study aims to apply the fuzzy analytic hierarchy process (FAHP) method to evaluate the priority of factors that constitute employee engagement with hotels. The theoretical review introduced and modeled five factors and 21 indicators. A pairwise comparison survey was designed and sent to experts, including university scientists, leaders of state management agencies in charge of tourism, and leaders of hotels. The research results show that the job characteristics factor is ranked as the first, the second factor is the working environment, the third factor is salary and welfare, the fourth factor is direct management, and the last ranking factor is the employee’s personality. Twenty-one indicators belonging to five factors were ranked through Liou and Wang’s (1992) method; the results showed that they ranked in the first three positions and had the most influence on hotel employee engagement as rated by experts, including recognizing employee efforts ranked first; the second factor is working together to achieve a common goal, and meaningful and purposive are ranked as the third factor. Meanwhile, the three factors with the lowest rankings, skills requirement, are ranked 19, the 20th place belongs to full facility, and the last place belongs to the sociable, enthusiastic, and friendly.