Fuzzy Technique For Order Of Preference By Similarity To Ideal Solution Research Articles

The effects of global product design on supply chain efficiency and natural resources management

The significance of global product design as a primary factor in determining supply chain efficiency and natural resource management. This study examines the impact of global product design changes on process and supply chain practices. Specifically, it seeks to understand in promoting sustainable practices across global supply chains. This study, utilizes the fuzzy Analytical Hierarchy Process (AHP) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods to evaluate the criteria, sub-criteria, and various significant opportunities influencing sustainable product design and supply chain management. The fuzzy AHP method is used to assess the key criteria and their respective sub-criteria. The fuzzy TOPSIS method is used to rank the opportunities in driving sustainable practices across global supply chains. The results of fuzzy AHP show that innovation and product differentiation (C4), economic viability (C1), and supply chain efficiency (C5) are the crucial criteria. While the results of fuzzy TOPSIS present that supply chain transparency (O2) is the most suitable opportunity, followed by circular economy practices (O1) and policy advocacy and compliance (O6) in adopting global product design on supply chain efficiency and natural resources management. Thus, this study is highly relevant to the governments, industry specialists, and policymakers who aim at enhancing the dynamic business environment and sustainable development.

Prioritizing environmental and policy factors and solutions in sustainable mineral resources management for green growth in China

AbstractIn the wake of the increasing environmental challenges and the urgent need for sustainable development, this study focuses on the complex issue of mineral resource management. Given the growing global demand for minerals and the environmental impact of extraction, the research seeks to uncover the solutions that promote green growth while effectively addressing the ecological consequences of resource utilization in China. In the study, six factors, twenty‐four sub‐factors, and five potential solutions have been identified influencing sustainable mineral resource management and green growth. The study utilizes fuzzy Analytical Hierarchy Process (AHP) to assess these factors and sub‐factors. Following, the study utilizes fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to evaluate and rank five potential solutions for sustainable development. The fuzzy AHP results indicate that environmental impact mitigation, robust policy frameworks, and innovation in extraction techniques are the most crucial factors. The fuzzy TOPSIS findings indicate that technological innovation for sustainability ranks highest, followed by policy‐driven green growth, socio‐economic empowerment, enhanced environmental stewardship, and integrated circular economy approaches. These findings emphasize the critical role of advanced technologies and robust policies in promoting sustainability while addressing the socio‐economic and environmental dimensions of mineral resource management.

Analysis of solution strategies for the transition to renewable energy in Saudi Arabia

The shift from fossil fuels to low-carbon energy solutions is crucial to mitigate the effects of climate change. The Kingdom of Saudi Arabia (KSA) has formulated a policy framework to accelerate the development of renewable energy (RE) as part of Vision 2030. Therefore, the transition to RE is vital for reducing dependence on fossil fuels and mitigating climate change. Nevertheless, critical barriers hinder RE adoption in the KSA. This study identified several main barriers, sub-barriers, and solution strategies for the analysis. Therefore, the fuzzy Analytical Hierarchy Process (AHP) method was incorporated to evaluate seven barriers and twenty-eight sub-barriers. Later, the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used to prioritize the nine solution strategies for adopting RE technologies in the KSA. The fuzzy AHP results emphasize that technological, environmental, and market barriers obstruct RE adoption. Fuzzy TOPSIS indicates that public awareness campaigns, energy subsidy reforms, and modernization of the energy grid are the most suitable solutions for the adoption of RE technologies in the KSA. Consequently, this research will help governments, stakeholders, and policymakers expedite RE adoption by determining these barriers and strategies to achieve the Saudi Vision 2030 goal.

Enhancing biometric system selection: A hybrid AHP-neutrosophic fuzzy TOPSIS approach

A biometric system is essential in improving security and authentication processes across a variety of fields. Due to multiple criteria and alternatives, selecting the most suitable biometric system is a complex decision. We employ a hybrid approach in this study, combining the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Analytic Hierarchical Process (AHP). Biometric technologies are ranked using the TOPSIS method according to the relative weights that AHP determines. By applying the neutrosophic set theory, this approach effectively handles the ambiguity and vagueness inherent in decision-making. Fingerprint, face, Iris, Voice, Hand Veins, Hand geometry and signature are the seven biometric technologies that are incorporated in the framework. Seven essential characteristics are accuracy, security, acceptability, speed and efficiency, ease of collection, universality, distinctiveness used to evaluate these technologies. The model seeks to determine which biometric technology is best suited for a particular application or situation by taking these factors into account. This technique may be applied in other domains in the future.

Evaluating music education interventions for mental health in Chinese university student: a dual fuzzy analytic method

This study addresses the growing anxiety and depression among Chinese university students by evaluating and ranking music education strategies to alleviate these issues. We integrates Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FAHP was utilized to determine the weight of factors such as academic pressures, social relationships, and cultural norms, while fuzzy TOPSIS ranked the effectiveness of music education interventions based on these weights. The results revealed that ‘Mental health stigma’ and ‘Academic Pressures and Rigidity’ are among the highest weighted factors, significantly impacting student anxiety. ‘Music Appreciation and Music-Based Self-Care’ emerged as the most effective strategy. These results highlight the importance of direct involvement in music-related activities for improving student mental health.

Evaluation and optimization of key performance indicators affecting adoption of the building information modeling and blockchain technology in Indian construction sector through fuzzy TOPSIS and genetic algorithm

Providing a better digital platform is one of the major concerns of the construction industry in Industry 4.0 era. In order to deal with vagueness and imprecision throughout the decision-making process, fuzzy set theory has been applied as one of the principal agents. This paper aims to identify the KPIs related to Building Information Modelling (BIM) and blockchain for a high-speed-rail-project also called as bullet-train project in India. The identified KPIs have been evaluated through a Multi-Criteria-Decision-Making (MCDM) technique like Fuzzy-Technique-for-Order-of-Preference-by-Similarity-to-Ideal-Solution (FTOPSIS) methodology. Furthermore, Genetic Algorithm (GA) has been applied to optimize the resources like manpower and equipment deployed in the bullet-train project which finally enable effective implementation of blockchain technology in construction projects. From the analysis, it has been observed that after application of GA for optimization the average potential savings in skilled manpower was 16.16%, unskilled manpower was 16.82% and equipment was 14.22%. After optimization through GA, overall, there may be a potential savings of 13% and 7.18% respectively in terms of project time and cost. Every activity has been time stamped, which would prevent any kind of manipulation in that activity during its billing.

Application of multi-criteria group decision-making for water quality management.

As waste discharge into numerous river systems escalates, the pollution of water bodies typically rises. Given the limited capacity of rivers to withstand pollution and their constrained self-cleaning capabilities, treated pollutants from waste discharge must be released into the river. Despite numerous models and algorithms proposed for managing river water quality to meet standards, literature, to our awareness, lacks the utilization of a comprehensive multi-criteria group decision-making approach for water quality management, particularly in river systems. Therefore, this research introduces a new, comprehensive multi-criteria group decision-making for the management of water quality in the Haraz River basin, located in Iran. To do so, the water quality of the basin, a one-dimensional water quality model, QUAL2Kw, was employed to simulate and calibrate the water quality along the river. The simulation results revealed that the downstream water quality violates the water quality standards. To mitigate this issue, various scenarios for waste load allocation (WLA) were evaluated, including no wastewater treatment, primary wastewater treatment, advanced secondary wastewater treatment utilizing the activated sludge (AS) method, and advanced wastewater treatment via the membrane bioreactor (MBR) method. Utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy TOPSIS group decision-making model, it was determined that the optimal solution was the implementation of secondary wastewater treatment utilizing the activated sludge method for the 11 PS of pollution, while still adhering to Iranian water quality standard. In addition, the findings of the present study indicate that the implementation of primary wastewater treatment, advanced secondary wastewater treatment utilizing AS, and advanced wastewater treatment through MBR within the study area led to a significant enhancement in water quality. This enhancement ranged from 35 to 105% across various scenarios when compared to conditions where no actions were taken to the treatment of water.

Investigation and Assessment the Level of Adoption Lean Philosophy in SMES Under Uncertainty by EFA/FAHP/FTOPSIS Integrated Model

Abstract Small and Medium Enterprises (SMEs), thus it is pursues to improve their performance to stay in the global competitive markets through adopting an efficient manufacturing systems, one of them is lean production (LP). LP is a continuous improvement philosophy that based on using various lean activities to improve enterprise performance by eliminating various type of waste. In this paper, a Lean Level Assessment Methodology is proposed which integrated Exploratory Factor Analysis (EFA), Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) to identify level of importance of lean activities and assess the level of SMEs leanness concerning five dimensions of lean activities. SMEs lean activities have surveyed through a comprehensive literature review, where twenty six lean activities have identified as the most common SMEs activities that classifying into five lean dimensions. A questionnaire was developed to collect data related to the levels of adoption of these lean activities by SMEs using a triple Likert scale. EFA was used to extract the most influencing lean activities on SMEs leanness based on questionnaire data. FAHP was used to determine the weights and the level of importance of these lean activities, while FTOPSIS was employed to investigate and assess the level of SMEs’ leanness related to the five lean dimensions activities. The proposed methodology has applied in four Iraqi SMEs (A1, A2, A3, and A4) for producing healthy water and soft drink in Baghdad. The results have explained that only 19 lean activities are the most influencing on SMEs leanness. Efficient manager is an important lean activity that has 58.90% level of importance. Although the four Iraqi SMEs have approximately acceptable level of leanness related the five lean dimensions, there is variation in adoption these lean dimensions activities by SMEs. SMEs management should develop a continuous improvement strategy based on utilizing SMEs’ efforts and resources to improve activities of the weaker dimension for improving their competitiveness and ensuring sustainability in the rapidly changing business environment. One limitation of this paper is the difficulty in obtaining data related to lean activities and their performance through SMEs’ processes and activities.

Evaluating modern intrusion detection methods in the face of Gen V multi-vector attacks with fuzzy AHP-TOPSIS.

The persistent evolution of cyber threats has given rise to Gen V Multi-Vector Attacks, complex and sophisticated strategies that challenge traditional security measures. This research provides a complete investigation of recent intrusion detection systems designed to mitigate the consequences of Gen V Multi-Vector Attacks. Using the Fuzzy Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), we evaluate the efficacy of several different intrusion detection techniques in adjusting to the dynamic nature of sophisticated cyber threats. The study offers an integrated analysis, taking into account criteria such as detection accuracy, adaptability, scalability, resource effect, response time, and automation. Fuzzy AHP is employed to establish priority weights for each factor, reflecting the nuanced nature of security assessments. Subsequently, TOPSIS is employed to rank the intrusion detection methods based on their overall performance. Our findings highlight the importance of behavioral analysis, threat intelligence integration, and dynamic threat modeling in enhancing detection accuracy and adaptability. Furthermore, considerations of resource impact, scalability, and efficient response mechanisms are crucial for sustaining effective defense against Gen V Multi-Vector Attacks. The integrated approach of Fuzzy AHP and TOPSIS presents a strong and adaptable strategy for decision-makers to manage the difficulties of evaluating intrusion detection techniques. This study adds to the ongoing discussion about cybersecurity by providing insights on the positive and negative aspects of existing intrusion detection systems in the context of developing cyber threats. The findings help organizations choose and execute intrusion detection technologies that are not only effective against existing attacks, but also adaptive to future concerns provided by Gen V Multi-Vector Attacks.

Assessing the impact of green finance on sustainable tourism development in China

The escalating urgency to address environmental degradation and promote sustainable development globally has emphasized the critical role of Green Finance (GF) in fostering responsible practices across industries. The tourism sector has drawn significant attention due to its substantial environmental impact, necessitating the implementation of robust financial mechanisms to mitigate its ecological footprint. China, recognized as a key player in the global tourism arena, the convergence of rapid economic expansion and the imperative for environmental conservation presents a distinctive set of challenges and opportunities. The study employed the Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies to systematically evaluate the impact of GF. The findings of fuzzy AHP indicate the critical role of environmental sustainability measures (GF2) as the topmost impacting factor. This refers to the practice of utilizing financial mechanisms and instruments to support initiatives that promote environmental conservation, minimize ecological footprints, and foster sustainable development. While financial allocation and effectiveness (GF1) and policy and regulatory framework impact (GF4) also hold significant importance in shaping sustainable tourism development. Moreover, the results of fuzzy TOPSIS identified top strategies such as green bond innovation for ecosystem regeneration (S1) and circular economy integration (S4), which can play a significant role in promoting sustainable tourism practices by facilitating initiatives aimed at ecosystem regeneration and integrating circular economy principles into the tourism industry.

Are Indian ports safe? Identifying, analysing and prioritizing the risks affecting India's major ports

Seaports are exposed to multiple risks that may affect security and operations. This research aims to develop a framework for identifying, ranking, and prioritizing the risks. Also, this study ranks the 12 major Indian ports based on the identified risk factors. The study follows an extensive literature review, prioritization by Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and sensitivity analysis for robustness. Thirty-two risks were identified and classified into five categories: natural disasters, geographical risks, security risks, operational and financial risks, and socio-political risks. The analysis suggests that the most important risk that the ports in India should consider is natural disasters. The risk of cyclones and tsunamis occupied the first two ranks among the global risks. Operational and financial risks, such as complex and lengthy approval procedures and infrastructure risks, are ranked third and fourth. Mumbai is ranked first as the riskiest Indian port, followed by Kolkata, JNPT (Jawaharlal Nehru Port Trust), and Vishakapatnam Port

A life cycle decision framework of China offshore wind turbines with ANP-Intuitionistic fuzzy TOPSIS method

In China, offshore wind energy is a popular source of green energy. Selecting offshore wind turbine design schemes is a decision problem based on multiple criteria. However, the selection is hardly made from the point of view of the life cycle due to the complex association of evaluation criteria, especially in the conceptual design stage. To solve this problem, a new multi-criteria decision-making framework for selecting the life cycle design scheme of offshore wind turbines is designed. The design information of the life cycle process of these turbines is expressed using Function-Structure-Material-Process-Transportation model in this framework. The life cycle evaluation index system of offshore wind turbines was established and mapped with this model to carry out rapid evaluation of various schemes. In light of this, an intuitive fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method based on analytic network process (ANP) was proposed to process fuzzy decision information and establish criteria correlation. Finally, a case study was conducted, and sensitivity and comparative analyses were carried out. The proposed method can effectively select the optimal scheme from six different design schemes for the life cycle of offshore wind turbines.

Integrated project delivery (IPD) capabilities on reducing claims in urban underground projects: A hybrid FAHP-FTOPSIS approach

Participatory planning practices - associated with integrated project delivery (IPD) can influence the cost and time claims of construction projects. However, there is a lack of research providing a quantitative holistic assessment of implementing IPD practices for reducing claims. In order to fill this knowledge gap, the present study aims to present a hybrid prioritization model to assess and mitigate the impact of claims on urban underground projects using IPD capabilities. The fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) methods are combined to prioritize traditional project delivery systems claims and rank IPD capabilities to reduce critical claims. FAHP identifies eight critical claims, including incorrect selection of the project contract system, lack of use of legal experts in setting contracts, exchange rate fluctuations and changes in currency conditions, lack of manpower skilled personnel in the region, ambiguities and shortcomings in the contract, restrictions on the supply of materials, machinery and equipment, delays in payments and financial obligations of the employer and lack of equipment and machinery appropriate to the type of work in the region. FTOPSIS ranks organizational and leadership, planning enhancement, and appropriate technology as the most effective capabilities in reducing claims. These capabilities should be implemented according to the obtained ranking to accept IPD in reducing the conventional claims future projects. The main innovation lies in the development of a hybrid prioritization framework to evaluate conventional contractual claims and rank IPD capabilities. The framework proposed in the study provides a valuable tool for construction managers to make informed decisions and mitigate the impact of contractual claims during the project delivery phase.

Conflicts due to cultural differences in multicultural ships

ABSTRACT The growth in global trade and technological developments in the maritime industry have increased the number of ships and their capacities. Despite the decreased size of crews in modern ships, the increased number of ships has increased the demand for qualified seafarers. Shipowners and ship operators have tried to solve the problem of this imbalance by employing seafarers, not only from their own countries, but also from other countries. Increased competition and costs have increased the number of multinational crews in the maritime trade. In ships operated with multinational crews, potential conflicts among the crewmembers due to cultural differences endanger the safety of the ship and the cargo. In this study, the literature was examined to identify conflicts due to cultural differences in multinational ships. The factors causing conflict were established as criteria by taking the opinions of human resources experts of eleven maritime enterprises and four academics, and the criteria weights were determined with the fuzzy AHP (analytic hierarchy process) method. The rankings of solution alternatives were calculated by the fuzzy TOPSIS (technique for order of preference by similarity to ideal solution) method.

Construction 4.0 technology evaluation using fuzzy TOPSIS: comparison between sustainability and resiliency, well-being, productivity, safety, and integrity.

This study aims to compare the impact of Construction 4.0 technologies on different organizational core values, focusing on sustainability and resiliency, well-being, productivity, safety, and integrity. To achieve that aim, the study objectives are the following: (i) identify the critical Construction 4.0 technologies between core values; (ii) appraise overlapping critical Construction 4.0 technologies between core values; (iii) examine the ranking performance of Construction 4.0 technologies between core values; and (iv) analyze the interrelationships between Construction 4.0 technologies and core values. First, twelve Construction 4.0 technologies were identified from a national strategic plan. Then, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) that incorporates subjective and objective weights was used to evaluate the impact of the Construction 4.0 technologies on the five core values. Finally, the collected data was analyzed using the following techniques: fuzzy TOPSIS, normalization, overlap analysis, agreement analysis, sensitivity analysis, ranking comparison, and Spearman correlation. The study findings reveal four critical Construction 4.0 technologies that enhance all five core values: building information modeling (BIM), Internet of Things (IoT), big data and predictive analytics, and autonomous construction. Also, there is a high agreement on the Construction 4.0 technologies that enhance well-being and productivity. Lastly, artificial intelligence (AI) has the highest number of very strong relationships among the core values. The originality of this paper lies in its comprehensive comparison of the impact of Construction 4.0 technologies on multiple organizational core values. The study findings provide valuable insights in making strategic decisions in adopting Construction 4.0 technologies.

Risk ranking of rig up operation activities using multi-criteria decision-making methods based on fuzzy environment

The main aim of this research study is to determine the risk ranking of 29 failure modes of rig-up operations using a well-known and highly effective MCDM method i.e. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). This method takes into account the four criteria which comprise human impact, property damage, environmental effect and company reputation as risk criteria. Three Experts in the field were invited to present the risk ranking of the relative importance of criteria and criteria performance of each risk (as failure mode) by utilizing linguistic variables which are then integrated in triangular fuzzy numbers for further analysis using the Fuzzy TOPSIS method. The evaluation concluded that FM20 (Collision between the offshore platform and boats) is the most dangerous risk with a coefficient of closeness (CCi) equal to 0.992 while the risk level of FM26 (foggy weather) was found least having a coefficient of closeness (CCi) of 0. Subsequently, sensitivity analysis of ranks concluded that FM1 (H2S inaccurate monitoring) is the most sensitive alternative with standard deviation and frequency of rank change was 5.16 and 15 respectively whereas FM20 (Collision between offshore platform and boats) is observed to be the least sensitive alternative. Fuzzy TOPSIS results were found in excellent correlations with the other reliable MCDM methods which include Fuzzy VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) and Fuzzy COPRAS (COmplex PRoportional ASsessment) yielding correlation of around 1. This study proves to be a landmark in the petroleum industry and significantly contributes to verifying safe practices, by taking appropriate actions in minimizing the risk level associated with different activities during rig-up operations.

Novel GIS-based fuzzy TOPSIS and filtration algorithms for extra-large scale optimal solar energy sites identification

Solar energy stands as an increasingly attractive and environmentally responsible energy source, possessing the potential to meet the burgeoning power needs of the Sarawak region. This paper proposes a novel methodology that combines Geographic Information System-based fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and filtration algorithms to identify the top 100 optimal Solar Energy Sites (SES). The research encompasses the extra-large scale potential SES comprising 19,237 coordinated data points. It evaluates SES based on 12 diverse criteria spanning climatic conditions, technical feasibility, accessibility, environmental considerations, and social factors. This research employs a meticulous double-layer filtration process to systematically eliminate unsuitable locations, resulting in a refined list of 1,862 potential SES. Subsequently, the fuzzy TOPSIS algorithm has further narrowed down the selection to the top 100 SES, constituting the core results of this research. The results reveal an interesting distribution of the identified SES, which mainly clustered in 3 huge categories (Kuching-Samarahan, Sibu-Kapit-Mukah and Bintulu-Miri). The identified 100 SES possess high closeness coefficients, which range from 0.7 to 0.85, where 1 indicates the best solution of the fuzzy TOPSIS algorithm. Additionally, the paper presents a spatial distribution analysis of the top-ranking sites across various divisions and districts. To validate the results obtained from the proposed model, a solar suitability map has been developed in ArcGIS Pro. When comparing the results from the proposed model to those obtained from the solar suitability map, most SES have consistent relative percentages, with only one SES falling below 50 %. To provide an overview of the similarity between the two models, the average relative percentage is computed at 69.01 %, signifying the proximity of SES to the optimal value of the solar suitability map. Furthermore, the developed source code in this research exhibits flexibility, featuring filtration algorithms that can accommodate any raster maps. It serves as an asset for researchers interested in conducting comprehensive large-scale SES identification in future case studies.

A fuzzy logic approach for selecting bearing ring materials in pharmaceutical applications

The present market trend of prioritizing safety and dependability at competitive rates has prompted the pharmaceutical and medical sectors to search more biocompatible, sustainable, and safe supplies. This paper seeks to achieve the most demanding criteria for pharmaceutical product safety, production capabilities, and performance standards. Hence, in order to avoid contamination, these sectors have set strict controls on the materials used in the manufacture of pharmaceutical and medical equipment. The purpose of this work is to introduce the FAHP-FTOPSIS technique, which offers an innovative and systematic way to selecting pharmaceutical bearing materials, filling research gaps, and enhancing pharmaceutical equipment design. The crucial issue of selecting appropriate bearing ring materials for pharmaceutical applications is addressed in this work. This research suggests the use of fuzzy logic as an innovative and successful technique to addressing this issue. Fuzzy logic is used to handle and evaluate linguistic data linked with the performance criteria of various materials such as PEEK, PTFE, Acetal, Stainless Steel, and Nylon6. A preference-based approach was used to conduct a comprehensive analysis of five commonly used materials for bearing rings. This included a direct comparison of different polymers, which are gaining favor in the pharmaceutical device sector, and stainless steel, that have traditionally been used for pharmaceutical equipment. The assessment was performed using the FAHP (Fuzzy Analytical Hierarchy Process), which assigned performance weight criteria as follows: C1 (0.128, 0.153, 0.139), C2 (0.082, 0.041, 0.019), C3 (0.425, 0.107, 0.371), C4 (0.528, 0.215, 0.089), C5 (0.137, 0.072, 0.036), C6 (0.092, 0.153, 0.172), C7 (0.063, 0.049, 0.032), C8 (0.048, 0.25, 0.049), and so on. Then, the FTOPSIS (Fuzzy Technique for Order of Preference by Similarity to Ideal Solution) was used to rank the alternatives, with the following results revealing the order: PEEK > Acetal > Nylon 6 > Stainless Steel > PTFE. This novel technology has the potential to improve the precision of material selection, therefore enhancing the overall efficiency and safety of pharmaceutical equipment and processes. The results clearly indicate that PTFE-based bearings surpass metallic ones in several aspects, including corrosion resistance, quiet operation, and minimal routine maintenance requirements. Remarkably, the calculated weight criteria align closely with the manufacturer's provided data. This innovative hybrid approach, combining FAHP (Fuzzy Analytical Hierarchy Process) and FTOPSIS (Fuzzy Technique for Order of Preference by Similarity to Ideal Solution), has the potential to simplify and optimize new product designs for pharmaceutical devices, reducing costs in the process. These findings highlight the efficacy of the FAHP-FTOPSIS technique in addressing the hitherto unexplored challenge of selecting suitable bearing component materials for specific applications. This approach offers a promising avenue for enhancing pharmaceutical device performance and reliability, marking a significant advancement in this field.

Analysis of factors and strategies for the implementation of sustainable tourism in a green economic structure in China

The tourism industry significantly contributes to the economic development of numerous emerging countries by facilitating the expansion of local enterprises. However, tourism may adversely affect the environment, local communities, and cultural heritage when it is not managed effectively. In this study, the case of Guilin city of China is undertaken for the analysis. Guilin, a popular tourist destination in southern China, has experienced rapid growth in tourism, generating economic benefits but also posing challenges related to environmental sustainability and social impact. This study uses Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify the most important criteria, sub-criteria, and effective policy strategies for promoting sustainable tourism in developing economies. Therefore, the study identified five criteria, twenty sub-criteria, and six policy strategies for sustainable tourism development in Guilin, China. The results of Fuzzy AHP method has identified economic viability, infrastructure and services, and social and cultural impact are the most suitable criteria for sustainable tourism. The results of Fuzzy TOPSIS method has recognized community-based tourism, sustainable tourism certification, and public-private partnerships as most effective strategies. This research provides useful insights for policymakers and stakeholders, enabling them to contribute to the sustainable development of the tourism industry and support the achievement of the United Nations sustainable development goals.

Determination of the most appropriate fertilizing method for apple trees using multi-criteria decision-making (MCDM) approaches.

Appropriate tree fertilization with essential nutrients is considered as one of the major factors in enhancing the quality and quantity of horticultural crops. The most efficient way to fertilize trees is to dig holes around the trunks and fill them with appropriate chemical and organic fertilizer. Doing this operation with mechanized methods reduces costs and increases productivity compared to traditional methods. In the present study, multi-criteria decision-making (MCDM) methods, including deterministic analytical hierarchy process (AHP) and fuzzy analytical hierarchy process (FAHP), technique for order of preference by similarity to ideal solution (TOPSIS), fuzzy TOPSIS (FTOPSIS), and analytic network process (ANP), were used to score and select the appropriate fertilizing method for apple trees based on the growers and expert's perspectives. The criteria, including fertilizing operation cost, crop yield, the percentage of tree damages, ease of entering and moving fertilizing equipment in tree rows, field capacity (with or without machinery), comfort and safety of fertilizing operations, after-sales service, access to the required machinery and implements, crop selling price, and crop quality, were used in the above-mentioned methods. The fertilization methods (Hole digging) considered in the present study were traditional fertilization (Shovel), orchard Trencher, motor hole digger, fixed centerline tractor-mounted hole digger, and off-set tractor-mounted hole digger. Based on the results, the priority of mechanized fertilizing methods was determined as tractor-mounted hole diggers (AHP weight of 0.286, FAHP weight of 0.285, TOPSIS relative proximity of 0.65, and FTOPSIS relative proximity of 0.64), fixed centerline tractor-mounted hole diggers (AHP weight of 0.219, FAHP weight of 0.158, TOPSIS relative proximity of 0.56, and FTOPSIS relative proximity of 0.62), motor hole diggers (AHP weight of 0.171, FAHP weight of 0.079, TOPSIS relative proximity of 0.46, and FTOPSIS relative proximity of 0.31), and orchard trenchers (AHP weight of 0.12, FAHP weight of 0.057, TOPSIS relative proximity of 0.19, and FTOPSIS relative proximity of 0.20), respectively. Based on the ANP method, off-set and fixed centerline tractor-mounted hole diggers had the highest priority (weights of 0.43 and 0.27), followed by trencher (weight of 0.16), motor hole diggers (weight of 0.09), and the traditional method (weight of 0.04). Results showed that applying orchard tractors equipped with mounted diggers, especially off-set types, can play an important role in enhancing the quantity and quality of apples produced, as well as reducing the costs of fertilizing operations.