Search

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

This paper aims to develop an integrated Quality–Cost–Environmental (QCE) indicator for the selection of photovoltaic panels (PVps) offered to customers, considering the following criteria: (i) quality satisfaction; (ii) cost-effectiveness; and (iii) environmental impact throughout the life cycle. The proposed QCE indicator was developed within a framework that incorporated an FAHP (Fuzzy Analytic Hierarchy Process), cost-effectiveness analysis (CEA), and life cycle assessment (LCA). The model test confirmed its effectiveness in choosing a PVp which combines environmental friendliness throughout its entire life cycle with satisfactory quality and a reasonable purchase price for customers. The proposed model can be utilized by individuals, businesses, and public entities for the selection of high-quality, cost-efficient, and environmentally friendly PVps—thereby promoting sustainable development. [ABSTRACT FROM AUTHOR]

The development and application of the industrial Internet platform (IIP) has brought enterprises huge benefits, such as improving the efficiency of resource management and equipment maintenance, achieving the precipitation and reuse of industrial knowledge, and enhancing the development ability of industrial APPs, etc. Therefore, in order to accelerate the application of the IIP, promote the digital transformation of enterprises, and enhance the application effect of the IIP, it is necessary to evaluate the application level and performance of the enterprise IIP. In this paper, taking the IIP in the power generation equipment industry as the research object, the background, architecture, and implementation process of the platform is described, and an evaluation method is proposed. First, a third-level evaluation index system is proposed via reference analysis and the Delphi method from four dimensions—platform basic condition, platform technology capability, platform application service capability, and platform input–output capability—and a total of sixty-five bottom indexes are designed in particular. Then, the fuzzy analytic hierarchy process (FAHP) and particle swarm optimization (PSO) algorithm are used to determine the weights of indexes, where FAHP is used to construct a fuzzy judgment matrix and PSO is adopted to adjust the consistency of the fuzzy judgment matrix in the FAHP. Finally, through the weights of indexes and questionnaire scores, the evaluation results are obtained, and the application level and performance of the IIP in the power generation equipment industry is analyzed. Through analysis, the important indexes that have a significant influence on the evaluation are determined, and the weaknesses that need to be enhanced are also pointed out, which can guide enterprises to make targeted improvements on the IIP in the power generation equipment industry so as to ensure the sustainable development of the power generation equipment industry. [ABSTRACT FROM AUTHOR]

Manufacturing companies face significant challenges due to rapid changes in globalized markets and open economies, which are experiencing mega-trends such as urbanization, globalization, and individualization. For sustainable growth, advanced technology is necessary. However, selecting technology is a difficult task due to the wide variety of options in the market. Technology has become a fundamental strategic factor for the growth and profitability of companies. The main objective of this paper is to propose a model and a methodological proposal for technology selection in the context of Industry 4.0 manufacturing. The proposed methodology is divided into three stages: The first stage is of knowledge and intervention, which allows for the socialization of the model and data collection. The second stage is the operational stage, where a hybrid method of FAHP and FANP is used to determine the weights of the factors considered. Lastly, the third stage is the analysis and evaluation stage, where the analysis, discussion, and evaluation of the results take place. To validate the proposed model, the methodology was applied to two case studies in Chilean industrial companies. The results obtained through the FAHP and FANP algorithms enabled decision makers to manage and select the most suitable technology from the wide variety of options available in today's markets. [ABSTRACT FROM AUTHOR]

Failure modes and effects analysis (FMEA) is a systematic approach that focuses on evaluating critical disturbances in a system. However, traditional FMEA has its own drawbacks, such as invalid computations and ambiguous priority definitions, which lead to many constraints in the application of complex production processes, especially in job shops with various resources. Therefore, this paper proposes an analytic disturbance prediction method for job shop with multiple resources and multiple evaluation indexes, which combines the vector computing techniques, FMEA, and fuzzy analytic hierarchy process (FAHP). In contrast to other work, this paper focuses on the establishment of FMEA mathematical model to improve the readability of multi-resource disturbance risk results. To this end, the projection of the disturbance vector is visualized to reduce repeated calculation results, triangles and trapezoids are used as membership functions to improve the accuracy of weight, and the differentiation index is used to reduce the ambiguity of priorities. The proposed method can effectively discover the critical disturbances and enable managers to undertake more assertive decisions. [ABSTRACT FROM AUTHOR]

The aim of the paper is to determine the risk level of a contract extension with the existing policyholders, which is further propagated to the business effectiveness and long-term sustainability of the company. The uncertainties in the relative importance of risk factors, their values, and risk levels are described by the linguistic forms, which are modeled by using the fuzzy sets theory. The evaluations of the relative importance of risk factors are stated as a fuzzy group decision-making problem. The weights of risk factors are obtained by using a fuzzy analytic hierarchy process. The determination of production rules for the assessment of the risk level is based on fuzzy IF-THAN rules. The verification of the model is performed by using real-life data originating from the insurance company which operates in the Republic of Serbia. [ABSTRACT FROM AUTHOR]

With the implementation of China's rural revitalization strategy, the construction of low-pollution villages has become an urgent demand for rural residents to achieve an ecologically livable environment. This paper aims to construct a new evaluation system for a "zero-pollution village" inspired by the principle of CASBEE. A village is regarded as a relatively independent ecosystem, and the evaluation system is designed to improve the "internal environmental quality Q" of a village while reducing the "external environmental load L". Thus, the evaluation system included two target strata (Q and L) and 3 layers comprising 6 criteria layers, 21 sub-criteria layers, and 76 indicators in the indicator layers. A new combined weight method based on FAHP-TOPSIS was presented to determine the weights of each layer of indicators. After verifying the evaluation system by applying it to 3 representative villages, 26 villages in Zhejiang Province were evaluated. These results indicate that the evaluation system was effective for evaluating the construction of a zero-pollution village. The current village environment in Zhejiang Province has been significantly improved; however, the vast majority of villages have not yet reached the zero-pollution standard. [ABSTRACT FROM AUTHOR]

Spring Outing Painting of Madam Guo is one of the representative works of Zhang Xuan, a famous Chinese court painter of the Tang dynasty (618–907), who was the "leader" of the trend of figure painting in the Tang dynasty and had a great influence on later figure painting. The costumes of the characters in the paintings not only show the artistic aesthetics of the prosperous Tang dynasty, but also reflect the rich cultural connotation. At present, the research on this painting is mainly about character discrimination and painting appreciation. There are few studies involving the costumes in this painting. With the rapid development of digital clothing technology, it provides a new way and path for the restoration of ancient costumes. Based on the costume archaeology of Spring Outing Painting of Madam Guo, this paper uses 3D virtual simulation and reverse engineering technology to restore the costume style of the characters in the picture, realize the digital restoration and protection of the style drawing, paper pattern, and 3D simulation drawing of the characters' costumes in the picture. Finally, we introduce the fuzzy analytic hierarchy process (FAHP) to comprehensively evaluate the costume restoration effect. Our proposed method solves the problem of the constraints of time and space on the presentation of ancient traditional costumes, promotes the excellent historical culture of China, and provides a certain reference for the modern redesign of ancient costumes. [ABSTRACT FROM AUTHOR]

Simple Summary: Considering the world's present pandemic situation, mHealth applications are essential for self-management of health. However, the recent growth of the healthcare industry provides various mHealth applications that result in difficulties for ordinary people in selecting the best application to fulfill their needs to their satisfaction. This research paper focuses on developing two hybrid decision-making methods, CODAS-FAHP and MOORA-FAHP, which may be used in assessing the usability of mHealth applications to monitor type 2 diabetes mellitus (T2DM) patients. The resulting analysis with the two hybrid models shows that the selection of mHealth applications can be done efficiently. People use mHealth applications to help manage and keep track of their health conditions more effectively. With the increase of mHealth applications, it has become more difficult to choose the best applications that are user-friendly and provide user satisfaction. The best techniques for any decision-making challenge are multi-criteria decision-making (MCDM) methodologies. However, traditional MCDM methods cannot provide accurate results in complex situations. Currently, researchers are focusing on the use of hybrid MCDM methods to provide accurate decisions for complex problems. Thus, the authors in this paper proposed two hybrid MCDM methods, CODAS-FAHP and MOORA-FAHP, to assess the usability of the five most familiar mHealth applications that focus on type 2 diabetes mellitus (T2DM), based on ten criteria. The fuzzy Analytic Hierarchy Process (FAHP) is applied for efficient weight estimation by removing the vagueness and ambiguity of expert judgment. The CODAS and MOORA MCDM methods are used to rank the mHealth applications, depending on the usability parameter, and to select the best application. The resulting analysis shows that the ranking from both hybrid models is sufficiently consistent. To assess the proposed framework's stability and validity, a sensitivity analysis was performed. It showed that the result is consistent with the proposed hybrid model. [ABSTRACT FROM AUTHOR]

Technology advancement in power–electronic interfaces and their evolution open an opportunity to end-users to benefit from their newfound capability. For the end-users, power–electronic interfaces can act as Distributed Energy Resources (DERs) for reactive power injection and absorption. If these power–electronic interface capabilities can be properly integrated into traditional utility system operations, they can be used as beneficial tools for distribution management and voltage profile enhancement. Considering the present distribution system, it is not possible to communicate to all DERs. In this paper, we considered two proposed residential-control and droop-control methods. The multi-criteria decision-making technique (MCDM), along with fuzzy theory, was used to prioritize candidate buses for their participation in the Volt-VAR program. In this paper, the contribution of active DERs in reactive power compensation was evaluated. [ABSTRACT FROM AUTHOR]

Assessing the sustainability of material-based products now encompasses social sustainability, a vital aspect often overlooked. Even though the existing frameworks provide a starting point, they do not often differentiate between the assessment criteria when making comparisons within one specific material category, which has made sustainability assessments more focused on environmental and economic aspects. This study addresses this critical gap by pioneering a social assessment framework curated to help practitioners to choose the most sustainable cement type out of the standard cement types used in the industry. Utilizing the Fuzzy Analytic Hierarchy Process (FAHP) and linear-scoring method, criteria weights were systematically assigned based on scoring by industry and academic experts. The findings highlight the importance of integrating social sustainability with environmental and economic factors in cement selection. Unlike traditional material selection, which primarily considers cost and performance, green material selection emphasizes the holistic impact of materials, including social factors. Variations in weightage decisions among experts highlight the influence of practical experience, research interests, and context. Functionality emerges as a crucial criterion. The ranking of cement types based on social scores places CEM II/B-M at the top, followed by CEM IV/A, CEM II/A-S, CEM II/A-V, CEM I, and CEM II/A-LL. The evolving nature of sustainability necessitates ongoing research to refine and expand existing frameworks for a more sustainable construction industry. [ABSTRACT FROM AUTHOR]

In response to the global demand for sustainable development in urban areas, there is an urgent need to enhance the ecological environment of urban areas. Urban renewal through sponge cities has become an effective method for achieving this goal. As one of the most dynamic elements in urban spaces, manhole covers play a crucial role in enhancing the city's image. To facilitate urban redevelopment effectively, improve the functionality of urban manhole covers, and promote sustainable urban development, this study explores ecological design factors for urban manhole covers, providing recommendations for future designs in China. Grounded on existing literature research and the urban redevelopment planning of the central district in Maanshan City, the FAHP method was used to determine the weights of five indicators containing environmental esthetics, ecological sustainability, intelligent detection, intelligent interaction, and safety, and scientifically constructed the ecological design and evaluation index system of intelligent grass pot manhole cover. The weighted average algorithm was used to obtain the index priority ranking, and the most critical elements were selected for design and refinement. The evaluation results indicate that safety, ecological sustainability, and the enhancement of the ecological design of intelligent manhole covers show the most significant improvement. The research outcomes can be used as a reference for enhancing urban ecological environments, promoting urban regeneration, and advancing sponge city construction. [ABSTRACT FROM AUTHOR]

In the context of increasing energy demands in Vietnam, and as a result of the limited supply of domestic energy (oil/gas/coal reserves are exhausted), the potential for renewable energy sources in Vietnam is significant. Thus, building wind power plants in Vietnam is necessary. Access to this type of renewable energy not only contributes to society's energy supply but also helps to save energy and reduce environmental pollution. Although some works have reviewed applications of the Multi-Criteria Decision Making (MCDM) model in wind power plant site selection, little research has focused on this problem in a fuzzy environment. This is the reason why a hybrid Fuzzy Analytic Hierarchy Process (FAHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are developed for wind power plant site selection in Vietnam. In the first stages of this research, an FAHP model is proposed for determining the weight of each potential location for building a wind power plant, based on qualitative and quantitative factors. A TOPSIS is applied for ranking all potential alternatives in the final stage. The authors collected data from seven locations, which have good conditions for investment in a wind power plant. The results indicate that Binh Thuan (Binh Thuan Province is located on coast of South Central Vietnam) is the best place for building a wind power plant in Vietnam. The contributions of this work proposed an MCDM approach under fuzzy environments for wind power plant location selection in Vietnam. This paper also resides in the evolution of a new approach that is flexible and practical for a decision-maker. This work also provides a useful guideline for wind power plant location selection in others countries. [ABSTRACT FROM AUTHOR]

With the rapid development of cloud computing, artificial intelligence, etc., data centers have become a flexible load due to their adjustable capabilities and are able to take on power service. However, the existing communication architecture is monolithic and poorly adapted between services and communications, which poses a challenge for data centers to participate in power service. Firstly, this article constructs a multi-domain communication architecture for data center management systems that includes local and remote communication, and analyzes the key technologies supporting this architecture. Secondly, based on differentiated service types and communication requirements, an evaluation system for the adaptability between service and communication technology was constructed, and a communication mode adaptation method based on fuzzy analytic hierarchy process (FAHP)-improved CRITIC combined weighting model and grey Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was proposed to achieve the analysis of the adaptability between differentiated service and multi-domain communication technology. According to the analysis of examples, the architecture and adaptation algorithm proposed in this article provide an effective theoretical basis and solution for the selection of multi-domain communication technologies for data center management system service. [ABSTRACT FROM AUTHOR]

The challenges resulting from rapid economic growth, urbanization, and increased motorization in developing nations necessitate a comprehensive and sustainable approach to urban public transport planning. While sustainable urban public transport (SUPT) planning offers a solution, the complexity of choosing suitable policy measure options remains a challenge. This study first introduces a decision support framework (DSF) that integrates the sustainable urban public transport manual (SUPTM) adopted for generating the potential SUPT policy measure options, the KonSULT knowledge base applied for providing the performance scores of each measure option for all determined criteria, and the HMADM (including FAHP, FSM, and TOPSIS) technique to create, rank, and select SUPT policy measure options tailored to medium-sized urban areas in developing nations. A case study of Khon Kaen City, Thailand, illustrates the practical application of the framework, resulting in a set of 31 (91.2%) out of the total of 34 ranked policy measure options. Comparing these prioritizations with the city's existing plan reveals a substantial agreement, which suggests the potential applicability of the DSF. Overall, the DSF marks a significant advancement in SUPT planning, which is crucial for shaping efficient, equitable, and environmentally conscious urban mobility in developing countries, which are undergoing transformative change. [ABSTRACT FROM AUTHOR]

In Vietnam, as more and more organizations are moving toward globalization, green supplier selection (GSS) has emerged as a strategic approach in supply chain management that requires supplier practices in lessening the environmental risks to society. Based on both conventional and environmental criteria, this paper aims to evaluate a set of suppliers by establishing a multi-criteria decision-making (MCDM)-based framework using an integrated fuzzy analytical hierarchy process (FAHP) with the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Initially, five GSS criteria of the environmental aspect (wastewater treatment, solid waste generation, energy consumption, air pollution, corporate social responsibility) and conventional criteria (quality, cost, delivery, and technology) are identified from the literature and consulting field experts to employ the MCDM approach. The trustworthiness of the proposed integrated framework is presented by discussing a case study in the coffee bean supply chain in Vietnam. The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts, and VIKOR is used to rank the alternatives against the selected criteria. From FAHP findings, the most important criteria are quantity discount, solid waste generation, order fulfillment rate, logistics cost, and purchasing cost. A consistency test is performed to ensure the uniformity of the expert's input. The best suppliers are determined through the final ranking of the VIKOR model for the case study. The work presented provides insight to decision-makers of supplier selection that helps determine significant GSS criteria and aids in the minimization of environmental risks to society arising from the supply chain on corporate sustainability standards. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of evaluating vehicle failure modes efficiently during the driving process. Generally, the most critical factors for preventing risk in potential failure modes are identified by the experience of experts through the widely used failure mode and effect analysis (FMEA). However, it has previously been difficult to evaluate the vehicle failure mode with crisp values. In this paper, we propose a novel hybrid scheme based on a cost-based FMEA, fuzzy analytic hierarchy process (FAHP), and extended fuzzy multi-objective optimization by ratio analysis plus full multiplicative form (EFMULTIMOORA) to evaluate vehicle failure modes efficiently. Specifically, vehicle failure modes are first screened out by cost-based FMEA according to maintenance information, and then the weights of the three criteria of maintenance time (T), maintenance cost (C), and maintenance benefit (B) are calculated using FAHP and the rankings of failure modes are determined by EFMULTIMOORA. Different from existing schemes, the EFMULTIMOORA in our proposed hybrid scheme calculates the ranking of vehicle failure modes based on three new risk factors (T, C, and B) through fuzzy linguistic terms for order preference. Furthermore, the applicability of the proposed hybrid scheme is presented by conducting a case study involving vehicle failure modes of one common vehicle type (Hyundai), and a sensitivity analysis and comparisons are conducted to validate the effectiveness of the obtained results. In summary, our numerical analyses indicate that the proposed method can effectively help enterprises and researchers in the risk evaluation and the identification of critical vehicle failure modes. [ABSTRACT FROM AUTHOR]

A precise evaluation of the actual situation is a significant aspect of making a correct and informed decision. Due to the bounded accuracy and elements of uncertainty in the data itself, a point estimate may be less adjusted and rough than an estimate based on fuzzy set theory. The stability of the Fuzzy AHP Arithmetic mean, Geometric mean, Extent analysis, and Lambda Max methods, widely used in practice, is verified. Three stages of verification are considered, investigating the impact of the following: (a) the scale applied; (b) methods of aggregation of the AHP matrices into the FAHP matrix; and (c) methods of combining several FAHP judgments. Slight changes in experts' estimates are programmatically simulated tens of thousands of times to track changes in ranking and deviations of results from the initial estimate. This continues the study of FAHP's stability due to the ambiguous results of such verification by the method of extent analysis. As a result of a comparative analysis of the listed evaluation methods, their specific features and advantages are identified. [ABSTRACT FROM AUTHOR]

In today's competitive environment, managing supply chains (SCs) is becoming increasingly challenging. Demand uncertainty, globalization, shorter product and technology lifespans, and growth in the number of logistics partners result in more sophisticated global supply relationships, which in turn, increase SC vulnerability. Generally, nervousness reduces SC effectiveness because SC instability is primarily caused by events that are external to the business domain. This tension creates uncertainty, increases the cost of maintaining supply chains, and makes relationships with suppliers and customers unpredictable. This study analyzed global SC nervousness (GSCN) components in terms of drivers, consequences, indicators, and pillars, and proposed solutions. A questionnaire was used to study and evaluate the characteristics of the GSCN, and the DELPHI–FAHP was used to analyze the results and designate the factors that most impact nervousness mitigation in the supply chain. To this end, a framework is presented to discuss the interactions of nervousness in a SC with an integrated solution. The results indicate that demand planning, sourcing strategy, collaboration, risk management, and sustainable SC, along with technological innovation applications, represent essential demands for a smarter future GSC vision. [ABSTRACT FROM AUTHOR]

This study evaluated the eco-geological environment quality of Hunjiang District, Baishan City, Jilin Province. Fifteen indicators were selected from geological, ecological, and social aspects to make the eco-geological environmental quality assessment more comprehensive. On the basis of improved game theory, two weighting methods of FAHP-CV (Fuzzy Analytic Hierarchy Process and Coefficient of Variation) were used to calculate the weight, and finally ArcGIS was used to intuitively understand the eco-geological environment quality of the study area. According to a threshold value, the eco-geological environment quality of the study area was divided into five types: better, good, medium, bad, and worse, and the results show that the overall eco-geological environment quality of the study area is in the middle and upper levels. The eco-geological environment quality of a small part of the area is poor. The classification of the eco-geological environment quality of Hunjiang District provides a scientific basis for the establishment of reasonable eco-geological environment protection and urban planning in the future. [ABSTRACT FROM AUTHOR]

In this paper, the application of hexagonal fuzzy multiple-criteria decision-making (MCDM) methodology for the site selection of electric vehicle charging stations is considered. In this regard, four factors and thirteen sub-factors have been taken into consideration for E-vehicle charging site selection. In this research, the geographic information system (GIS) has been incorporated with MCDM techniques. The fuzzy analytic hierarchy process (FAHP) is used to obtain a fuzzy weight of factors and sub-factors. MCDM tools fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) and fuzzy complex proportional assessment (FCOPRAS) have been used to rank the selected sites. A centroid-based method for defuzzification and distance measure between two hexagonal fuzzy numbers (HFN) has been developed for this paper. A practical example in Howrah, India, is considered to show the applicability and usefulness of the model. The results depict the suitability of the proposed research. Comparative and sensitivity analyses have been demonstrated to check the reliability, robustness and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

High competition between universities has been increasing over the years, and stimulates higher education institutions to attain higher positions in the ranking list. Ranking is an important performance indicator of university status evaluation, and therefore plays an essential role in students' university selection. The ranking of universities has been carried out using different techniques. Main goal of decision processes in real-life problems is to deal with the symmetry or asymmetry of different types of information. We consider that multi-criteria decision making (MCDM) is well applicable to symmetric information modelling. Analytic hierarchy process (AHP) is a well-known technique of MCDM discipline, and is based on pairwise comparisons of criteria/alternatives for alternatives' evaluation. Unfortunately, the classical AHP method is unable to deal with imprecise, vague, and subjective information used for the decision making process in complex problems. So, introducing a more advanced tool for decision making under such circumstances is inevitable. In this paper, fuzzy analytic hierarchy process (FAHP) is applied for the comparison and ranking of performances of five UK universities, according to four criteria. The criteria used for the evaluation of universities' performances are teaching, research, citations, and international outlook. It is proven that applying FAHP approach makes the system consistent, and by the calculation of coefficient of variation for all alternatives, it becomes possible to rank them in prioritized order. [ABSTRACT FROM AUTHOR]

In recent years, the market of textile and garment materials has been volatile, and the ongoing US-China trade war is creating good opportunities for other markets such as Vietnam, Bangladesh and Mexico to continue to expand their market share in the United States. Vietnam is expected to have great advantages thanks to cheap labor cost and strong production capacity. Raw material supplier selection in a volatile competitive environment is crucial for a company to succeed, and supplier selection is a complicate process in which decision-makers must consider multiple quantitative and qualitative features, along with their symmetrical impact, in order to achieve an optimal result. The purpose of selecting the right supplier is to improve competitiveness and product quality, while satisfying customer demand at a minimum production cost. The aim of this paper is to propose a multicriteria decision making model (MCDM) for garment and textile supplier selection. In the first stage, all criteria affecting this process are defined by using the supply chain operations reference model (SCOR) and experts' opinion. Incorporating hybrid fuzzy set theory into the analytical network process (ANP) model is the most effective tool for addressing complex problems of decision-making, which has a connection with various qualitative criteria; thus, the Fuzzy Analytical Hierarchy Process (FAHP) was applied for determining the weight of all potential suppliers, and the preference ranking organization method for enrichment of evaluations (PROMETHEE II) was used for ranking the supplier. The results of this research will assist researchers and decision makers in identifying, adapting and applying appropriate methods to identify the optimal material suppliers in the textile and garment industry. This research can also be used to support supplier selection decisions in other industries. [ABSTRACT FROM AUTHOR]

The urban mobility system is an important factor in social development and must, therefore, be tackled in a way that enables balanced, sustainable development. The purpose of the present work was to introduce a new holistic approach to urban mobility system (UMS) planning, which involves a strategic decision-making process with a broad involvement of various stakeholders. For this purpose, an innovative model was created by synthesizing the focus group (FG) method with the nominal group technique (NGT), SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, and the fuzzy analytical hierarchical process (FAHP) method. The fuzzy approach was chosen for its ability to incorporate imprecise and vague information and make a decision-making UMS process more realistic. Accordingly, the objective of the paper was to propose a newly developed model that will (considering the integration of various urban mobility subsystems) enable the detection, identification, and ranking of key priorities required for a more holistic approach to UMS planning. The results revealed that the developed integrated model enables acquired areas to be ranked according to priorities, which further allows the development of scenarios. Moreover, the model allows a better understanding of how to search for compromises when one is faced with multi-criteria decision-making and coordination of frequently contradictory goals. A new integrated urban mobility model, as proposed herein, was also successfully tested in a real-life application, which proves its potential for use in sustainable urban mobility planning in a holistic way. [ABSTRACT FROM AUTHOR]

Recently, risk assessment has become one of the most challenging issues in the areas of construction and public-private partnerships (PPPs). To address risk assessment issues, various decision-making techniques have been proposed, each with its own specific disadvantages and advantages. This paper investigates step-wise weight assessment ratio analysis (SWARA), complex proportional assessment (COPRAS), fuzzy analytic network process (FANP), fuzzy analytic hierarchy process (FAHP), fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS), simple additive weighting (SAW) and evaluation based on distance from average solution (EDAS) in order to define how various multi-attribute decision-making (MADM) methods compare when used for risk assessment in PPP projects. For this study, 5 risk assessment criteria and 10 types of risk used in Iranian highway PPP projects were selected. Four suitability and applicability tests were used to measure agreement between the rankings derived from the MADM methods. Final results show that all techniques had approximately the same rankings of risk assessment, with the SWARA, COPRAS, and EDAS methods performing slightly better. The findings of this study will help the parties in PPP and construction projects to select the best risk assessment method. [ABSTRACT FROM AUTHOR]

Accompanied by the concept of supply-side structural reform and conversion of new and old driving energy to create a new round of economic development in China, cement supplier evaluation and selection are increasingly crucial for concrete production plants, ensuring not only raw material supply with high quality and at a reasonable price but also sustainable and long-term cooperation with suppliers. Given the limitations of the existing approaches, this study proposes a cement supplier evaluation and selection framework based on the combination of the improved FAHP-CRITIC method and VIKOR method. We first develop a cement supplier evaluation and selection index system under the background of new and old driving energy conversion, including eight first-level indicators and twenty-one second-level indicators. The proposed model then uses triangular fuzzy numbers AHP (TFN-AHP) and the improved CRITIC method to calculate subjective and objective weights by replacing the coefficient of variation with standard deviation, uses the ideal solution-based method to determine their combination weights, and combines the VIKOR method to calculate the comprehensive evaluation values of candidate cement suppliers. After that, the proposed approach is applied to evaluate and select ten cement suppliers for concrete production plants, and the results are compared and analyzed with those using the traditional method. The results of the comparison show that the proposed strategy can be scientific and reliable, helping managers to make the right decision under the background of new and old driving energy conversion in China. [ABSTRACT FROM AUTHOR]

With the rapid development of new technologies, such as automation, big data, and artificial intelligence, a port that utilizes these technologies can significantly improve its operational efficiency and make it economically more competitive. Despite its increasing importance, there is no standard definition of a smart port, resulting in each country having its own smart port development strategy. In this study, we explore how varied port governance of port authorities may impact the smart port development strategy. First, we established a set of evaluation criteria, using the Borda count and fuzzy analytic hierarchy process, to obtain the key indicators for the development of smart ports in Taiwan. Then, we compared the preferred indicators of Taiwan's smart port development strategy with those of Spanish ports. An obvious difference in this ranking comparison is found. This indicates that Taiwan's strategy focuses on optimizing maritime safety, while Spain's strategy focuses on improving operational economics. Finally, we analyzed the differences between the smart port development strategies of these two countries using the latest port governance classification table. The results of the above analysis are also verified by comparing the differences in port legislation between them. It turns out that the private sector is deeply involved in the operation of ports in Taiwan compared with Spain. Our main contribution lies in providing a clear pathway for developing a smart port in Taiwan in the future and investigating the reasons for different smart port development strategies in different countries. [ABSTRACT FROM AUTHOR]

In the current scenario, climatic adversities and a growing population are adding woes to the concerns of food safety and security. Furthermore, with the implementation of Sustainable Development Goal (SDG) 12 by the United Nations (UN), focusing on sustainable production–consumption, climatic vulnerabilities need to be addressed. Hence, in order to map the sustainable production–consumption avenues, agricultural practices need to be investigated for practices like Climate-Smart Agriculture (CSA). A need has arisen to align the existing agricultural practices in the developing nation towards the avenues of CSA, in order to counter the abrupt climatic changes. Addressing the same, a relation hierarchical model is developed which clusters the various governing criteria and their allied attributes dedicated towards the adoption of CSA practices. Furthermore, the developed model is contemplated for securing the primacies of promising practices for the enactment of CSA using the duo of the Analytical Hierarchical Process (AHP) and Fuzzy AHP (FAHP). The outcomes result in the substantial sequencing of the key attributes acting as a roadmap toward the CSA. This emphasizes the adoption of knowledge-based smart practices, which leaps from the current agricultural practices toward the CSA. Furthermore, by intensifying the utilization of the improved and resilient seed varieties and implying the fundamentals of agroforestry, we secure primacy to counter the adversities of the climate. [ABSTRACT FROM AUTHOR]

The period of industrialization and modernization has increased energy demands around the world. As with other countries, the Taiwanese government is trying to increase the proportion of renewable energy, especially solar energy resources. Thus, there are many solar power plants built in Taiwan. One of the most important components of a solar power plant is the solar panel. The solar panel supplier selection process is a complex and multi-faceted decision that can reduce the cost of purchasing equipment and supply this equipment on time. In this research, we propose fuzzy MCDM approach that includes fuzzy analytical hierarchy process model (FAHP) and data envelopment analysis (DEA) for evaluation and selection of solar panel supplier for a photovoltaic system design in Taiwan. The main objective of this work is to design a fuzzy MCDM approach for solar panel supplier selection based on qualitative and quantitative factors. In the first step of this research, FAHP is applied to define the priority of suppliers. The AHP combined with fuzzy logic (FAHP) can be used to rank suppliers; however, the disadvantages of the FAHP model is that input data, expressed in linguistic terms, depends on experience of experts and the number of suppliers is practically limited, because of the number of pairwise comparison matrices. Thus, we applied several DEA models for ranking potential suppliers in the final stages. As the result, decision making unit 1 (DMU 1) is the optimal solar panel supplier for photovoltaic system design in Taiwan. The contribution of this research is a new fuzzy MCDM for supplier selection under fuzzy environment conditions. This paper also lies in the evolution of a new approach that is flexible and practical to the decision maker. It provides a useful guideline for solar panel supplier selection in many countries as well as a guideline for supplier selection in other industries. [ABSTRACT FROM AUTHOR]

The application of multiple criteria decision-making methods (MCDM) is aimed at choosing the best alternative out of the number of available versions in the absence of the apparently dominant alternative. One of the two major components of multiple criteria decision-making methods is represented by the weights of the criteria describing the considered process. The weights of the criteria quantitatively express their significance and influence on the evaluation result. The criterion weights can be subjective, i.e., based on the estimates assigned by the experts, and the so-called objective, i.e., those which assess the structure of the data array at the time of evaluation. Several groups of experts, representing the opinions of various interested parties may take part in the evaluation of criteria. The evaluation data on the criterion weights also depend on the mathematical methods used for calculations and the estimation scales. In determining the objective weights, several methods, assessing various properties or characteristics of the data array’s structure, are usually employed. Therefore, the use of the procedures, improving the accuracy of the evaluation of the weights’ values and the integration of the obtained data into a single value, is often required. The present paper offers a new approach to more accurate evaluation of the criteria weights obtained by using various methods based on the idea of the Bayes hypothesis. The performed investigation shows that the suggested method is symmetrical and does not depend on the fact whether a priori or posterior values of the weights are recalculated. This result is the theoretical basis for practical use of the method of combining the weights obtained by various approaches as the geometric mean of various estimates. The ideas suggested by the authors have been repeatedly used in the investigation for combining the objective weights, for recalculating the criteria weights after obtaining the estimates of other groups of experts and for combining the subjective and the objective weights. The recalculated values of the weights of the criteria are used in the work for evaluating the quality of the distant courses taught to the students. [ABSTRACT FROM AUTHOR]

Most countries depend on coal-fired thermal power plants (CTPPs) to meet energy demands. However, the adverse environmental impacts of CTPPs also remain a major concern. As the energy generations from renewable energy resources are still in the developing stage, reliance on CTPPs is inevitable. Hence, the efficiency of CTPPs has to be improved, while decreasing carbon emissions. This study aims to identify and evaluate the key factors that need to be addressed in improving the performance and minimizing the carbon emission of CTPPs. With the literature review and industrial interaction, twenty-four key factors are identified. Next, an integrated approach of the fuzzy analytic hierarchy process (FAHP) and fuzzy decision-making and trial laboratory (FDEMATEL) is used to evaluate the key factors. FAHP prioritizes the key factors and FDEMATEL reveals the relationship among the key factors. Results indicate air preheater leakage, plugging by ash, high levels of air ingress, air preheater secondary fire, and high levels of corrosion as the top five key factors affecting CTPP performance. Based on the outcome, the study offers some implications that may assist the industrial management in taking timely actions in improving the performance of CTPPs. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has boosted the growth of the online food delivery (OFD) market in every corner of the world. In Vietnam, the food delivery service is rising rapidly and opening a large gateway of opportunities for numerous OFD platforms, also making it a competing business market in this country. Thus, to keep up with the ever-changing market dynamics, there are numerous measures and dimensions for the OFD entrepreneurs to take into consideration towards sustainable development. This paper's objective is to evaluate major OFD companies in Vietnam based on a comprehensive set of criteria, which are social and environmental criteria (healthy and safety, information security, and environmental impact), economic criteria (delivery cost, operational capability, and risk management), service quality (order fulfillment, delivery speed, convenience of payment, online/offline service level, and customer feedback), and technology (web design, real-time tracking systems, and marketing techniques). To achieve this objective, this work proposes a multi-criteria decision-making (MCDM)-based framework combining the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS). The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts. Then, WASPAS is used to rank the OFD companies against the selected criteria. The evaluation criteria that have obtained maximum weight priority in the FAHP analysis are "convenience of payment", "delivery speed", "online service level", "order fulfillment", and "delivery cost". From the final ranking of WASPAS, Foody is today the best performing OFD player in Vietnam regarding the selected criteria, followed by GrabFood and Now. The proposed methodology can be an accurate and robust evaluation model for the industry, while the managerial implications of this study provide significant materials for decision-makers in the OFD market in improving their businesses towards sustainable development. [ABSTRACT FROM AUTHOR]

With the effects of the COVID-19 pandemic, the e-commerce trend is driving faster, significantly impacting supply chains around the world. Thus, the importance of logistics and supply chain functions has been amplified in almost every business that ships physical goods. In Vietnam, the logistics service sector has seen rapid expansion. Since more and more businesses are seeking third-party logistics (3PL) providers to outsource the logistics functions, this article aims to offer decision-makers an integrated and consistent model for evaluating and selecting the most efficient 3PLs. To this end, the authors exploit a hybrid multi-criteria method which is fuzzy analytic hierarchy process (FAHP) and fuzzy vlsekriterijumska optimizacija i kompromisno resenje (FVIKOR) while examining the most influential and conflicting criteria regarding economic, service level, environmental, social, and risk aspects. Fuzzy information in the natural decision-making process is considered, linguistic variables are used to mitigate the uncertain levels in the criteria weights. First, FAHP (the weighting method) is adopted to evaluate and calculate each criterion's relative significant fuzzy weight. FVIKOR (the compromised ranking method) is then used to rank the alternatives. The combination of FAHP and FVIKOR methods provides more accurate ranking results. As a result, reliability and delivery time, voice of customer, logistics cost, network management, and quality of service are the most impactful factors to the logistics outsourcing problem. Eventually, the optimized 3PLs were determined that fully meet the criteria of sustainable development. The developed integrated model offers the complete and robust 3PLs evaluation and selection process and can also be a powerful decision support tool for other industries. [ABSTRACT FROM AUTHOR]

Choosing a supplier is a complex decision-making process that can reduce the total cost of production inputs and increase profits without increasing the price or sacrificing product quality. However, supplier selection processes usually involve multiple quantitative and qualitative criteria which increase the complexity of the problem and may decrease the accuracy and effectiveness of the process. Such complex decision-making problems can be supported by using multicriteria decision-making (MCDM) models. While there have been multiple MCDM models to support supplier selection processes in different industries and sectors, only a few are developed to support the supplier selection processes in the garment industry, especially under uncertain decision-making environment. This paper presents an integrated mathematical model under a fuzzy environment and applies it to the supplier selection process in the garment industry. In this research, the authors utilize the Buckley extension based fuzzy Analytical Hierarchical Process (FAHP) method in combination with linear normalization based fuzzy Grey Relational Analysis (F-GRA) method to develop a MCDM approach to the supplier selection process under a fuzzy environment. As a result, supplier 08 (SA08) is the optimal supplier. The contribution of this work is to propose an MCDM model for ranking potential suppliers in the garment industry under a fuzzy environment. The proposed approach can also be applied to support complex decision-making processes under a fuzzy environment in different industries. [ABSTRACT FROM AUTHOR]

Companies are facing cut throat competition and are forced to continuously perform better than their competitors. In order to enhance their position in the competitive world, organizations are improving at a faster pace. Industrial organizations must be used to the new ideals, such as innovation. Today, innovative design in the development of new products has become a core value in most companies, while innovation is recognized as the main driving force in the market. This work applies the Russian theory of inventive problem-solving, TRIZ and the fuzzy analytical hierarchy process (FAHP) to design a new shape for machine tools. TRIZ offers several concepts and tools to facilitate concept creation and problem-solving, while FAHP is employed as a decision support tool that can adequately represent qualitative and subjective assessments under the multiple criteria decision-making environment. In the machine tools industry, this is the first study to develop an innovative design under the concept of lean production. We used TRIZ to propose the relevant principles to the shape's design with the innovative design consideration and also used FAHP to evaluate and select the best feasible alternative from independent factors based on a multiple criteria decision-making environment. To develop a scientific method based on the lean production concept in order to design a new product and improve the old designing process is the contribution of this research. [ABSTRACT FROM AUTHOR]

In order to improve the user experience of public fitness equipment, based on the principles of experience design principle, the Norman 3-level theory is used to obtain product materials, using safety, equipment practicality, product interest, and humanistic construction experience. The 5-level Likert evaluation scale is used to conduct a satisfaction survey on the index factors. According to the score, the fuzzy comprehensive evaluation method is applied to calculate the weights and average satisfaction values of the first and second indexes and discover the practical characteristics, interesting characteristics, and humanities of users. The characteristic satisfaction is low. The IPA model is used to analyze and evaluate the position of each evaluation index factor quadrant, and the experience factors that need improvement are obtained. In view of the analysis results, suggestions for advancement of public fitness equipment and factors in urgent need of improvement are put forward, and the safety experience refine design of the stroller is provided, which offers an effective reference for the experience design of public fitness equipment. [ABSTRACT FROM AUTHOR]

Globally, increasing environmental issues are gaining attention to facilitate the adoption of green innovation for sustainable supply chain management (SSCM). Sustainable environmental practices have been well-considered in the literature; however, no study has focused on adopting green innovation practices for sustainable development. Thus, environmental management authorities are putting pressure on industries to implement green innovation criteria for SSCM operations. Moreover, it is important to select traditional suppliers to transform its practices to that of sustainable supply chains in order to achieve the industry's sustainable supply chain goals. In response, this research identified and analyzed the green innovation criteria for SSCM and then selected a supplier that could implement green aspects in the SSCM. This study developed an integrated multi-criteria decision making (MCDM) model using the fuzzy analytical hierarchy process (FAHP) and the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The objective of this study was to analyze suppliers to implement green innovation criteria for SSCM practices in the textile manufacturing companies of China. This study reviewed and identified three green innovation criteria and seventeen sub-criteria. Then, the FAHP technique was employed to analyze and rank green innovation criteria and sub-criteria. Finally, the FTOPSIS method was used to investigate and rank eight suppliers. The findings of the FAHP indicated that economic (EC) criteria were the most vital green innovation criteria in the SSCM. Furthermore, the FTOPSIS results revealed that supplier 5 was the most suitable supplier for implementing green innovation criteria in the SSCM. These findings will help managers, practitioners, and policymakers implement green innovation criteria in sustainable manufacturing supply chains. [ABSTRACT FROM AUTHOR]

Landslides are one of the most detrimental geological disasters that intimidate human lives along with severe damages to infrastructures and they mostly occur in the mountainous regions across the globe. Landslide susceptibility mapping (LSM) serves as a key step in assessing potential areas that are prone to landslides and could have an impact on decreasing the possible damages. The application of the fuzzy best-worst multi-criteria decision-making (FBWM) method was applied for LSM in Austria. Further, the role of employing a few numbers of pairwise comparisons on LSM was investigated by comparing the FBWM and Fuzzy Analytical Hierarchical Process (FAHP). For this study, a wide range of data was sourced from the Geological Survey of Austria, the Austrian Land Information System, Humanitarian OpenStreetMap Team, and remotely sensed data were collected. We used nine conditioning factors that were based on the previous studies and geomorphological characteristics of Austria, such as elevation, slope, slope aspect, lithology, rainfall, land cover, distance to drainage, distance to roads, and distance to faults. Based on the evaluation of experts, the slope conditioning factor was chosen as the best criterion (highest impact on LSM) and the distance to roads was considered as the worst criterion (lowest impact on LSM). LSM was generated for the region based on the best and worst criterion. The findings show the robustness of FBWM in landslide susceptibility mapping. Additionally, using fewer pairwise comparisons revealed that the FBWM can obtain higher accuracy as compared to FAHP. The finding of this research can help authorities and decision-makers to provide effective strategies and plans for landslide prevention and mitigation at the national level. [ABSTRACT FROM AUTHOR]

Vietnam's garment industry is facing many challenges, including domestic competition and the global market. The free trade agreement, which Vietnam signed, includes environmental barriers, sustainable development, and green development. The agreement further requires businesses to make efforts to improve not only product quality but also the production process. In cases when enterprises cause environmental pollution in the production process and do not apply solutions to reduce waste, save energy, and natural resources, there is a risk of no longer receiving orders or orders being rejected, especially orders from the world's major branded garment companies. In this research, the authors propose a multicriteria decision-making model (MCDM) for optimizing the supplier evaluation and selection process for the garment industry using sustainability considerations. In the first stage of this research, all criteria affecting supplier selection are determined by a triple bottom line (TBL) model (economic, environmental, and social aspects) and literature reviews; in addition, the fuzzy analytic hierarchy process (FAHP) method was utilized to identify the weight of all criteria in the second stage. The technique for order preference by similarity to an ideal solution (TOPSIS) is a multicriteria decision analysis method, which is used for ranking potential suppliers in the final stage. As a result, decision-making unit 10 (DMU/10) is found to be the best supplier for the garment industry. The contribution of this research includes modeling the supplier selection decision problem based on the TBL concept. The proposed model also addresses different complex problems in supplier selection, is a flexible design model for considering the evaluation criteria, and is applicable to supplier selection in other industries. [ABSTRACT FROM AUTHOR]

In addition to its potential for wave power, wind power, hydropower, and solar power, it can be said that Vietnam is a country with great potential for biomass energy derived from agricultural waste, garbage, and urban wastewater, which are resources widely available across the country. This huge amount of biomass, however, if left untreated, could become a major source of pollution and cause serious impacts on ecosystems (soil, water, and air), as well as on human health. In this research, the authors present a fuzzy multicriteria decision-making model (FMCDM) for optimizing the site selection process for biomass power plants. All of the criteria affecting location selection are identified by experts and literature reviews; in addition, the fuzzy analytic hierarchy process (FAHP) method was utilized so as to identify the weight of all of the criteria in the second stage. Furthermore, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is applied for ranking potential locations in the final stage of this research. As a result, Long An (DMU/005) was found to be the best location for building biomass energy in Vietnam. The main contributions of this work include modeling the site selection decision process under fuzzy environment conditions. The proposed approaches also can address the complex problems in site selection; it is also a flexible design model for considering the evaluation criteria, and is applicable to location selection for other industries. [ABSTRACT FROM AUTHOR]