Search Results (105)

In the later stages of oilfield development, the decline in oil well production and the increase in development costs, attributed to issues such as insufficient liquid supply, necessitate the implementation of intermittent pumping measures. However, current methods for selecting these wells lack comprehensiveness in the decision-making process. This article proposes a novel method for selecting intermittent pumping wells utilizing the analytic network process (ANP) and fuzzy logic. Initial surveys identified the main factors influencing intermittent pumping effectiveness. The ANP was employed to screen and integrate six core factors, including submergence depth and water cut. Subsequently, a fuzzy-logic-based model was developed, incorporating trapezoidal and rectangular membership functions to establish detailed correlations among the factors. The model’s efficacy was validated and tested using real-world data from the oilfield. Results indicate that the model’s assessments of intermittent pumping wells align closely with professional engineering judgments. This approach not only provides clear guidance for well selection but also demonstrates high scalability and adaptability across different oilfields by adjusting membership functions, thereby showcasing significant practical value. Full article

The risk of both fatal accidents and non-fatal injuries in the construction industry is significantly high in most countries. To reduce this construction safety risk, the proper use of personal protective equipment (PPE) is one of the major measures on the jobsite. In this research, in order to comprehensively assess the PPE plans, a three-phase framework was proposed to identify the optimal solution for PPE planning from a set of alternatives. As a result, four main criteria and fifteen sub-criteria were identified based on a systematic literature review, and a decision-making model integrating the analytic network process (ANP) and VIekriterijumsko KOmpromisno Rangiranje was developed. As the assessment information in the survey was incomplete and vague, the fuzzy sets theory was adopted to transform the linguistic terms into fuzzy numbers for evaluation. The model further calculated the weight of each criterion and prioritized the potential PPE plan alternatives. Finally, the presented model was implemented in a case study to verify its feasibility and applicability for practical construction management. The proposed method enables the selection of the most compromising solution as the optimal PPE plan. This research assists decision-makers and safety planners at construction workplaces to improve the overall safety performance and reduce accident risks, which significantly contributes to construction safety management and practice. Full article

Autonomous vehicles (AVs) must fulfill adequate safety requirements before formal application, and performing an effective functional evaluation to verify vehicle safety requires extensive testing in different scenarios. However, it is crucial to rationalize the application of different scenarios to support different testing needs; thus, one of the current challenges limiting the development of AVs is the critical evaluation of scenarios, i.e., the lack of quantitative criteria for scenario design. This study introduces a method using the Spherical Fuzzy-Analytical Network Process (SF-ANP) to evaluate these scenarios, addressing their inherent risks and complexities. The method involves constructing a five-layer model to decompose scenario elements and using SF-ANP to calculate weights based on element interactions. The study evaluates 700 scenarios from the China In-depth Traffic Safety Study–Traffic Accident (CIMSS-TA) database, incorporating fuzzy factors and element weights. Virtual simulation of vehicles in the scenarios was performed using Baidu Apollo, and the performance of the scenarios was assessed by collecting the vehicle test results. The correlation between the obtained alternative safety indicators and the quantitative values confirms the validity and scientific validity of this approach. This will provide valuable guidance for categorizing audiovisual test scenarios and selecting corresponding scenarios to challenge different levels of vehicle functionality. At the same time, it can be used as a design basis to generate a large number of effective scenarios to accelerate the construction of scenario libraries and promote commercialization of AVs. Full article

The objective of this study is to enhance the resilience of the coal-to-liquids (CTL) industrial chain and supply chain to withstand increasing shock pressures. There is an urgent need to improve the resilience of the industrial chain and supply chain. This paper identifies 21 resilience-influencing factors from 4 perspectives: absorption capacity, adaptability, recovery capacity, and self-learning capacity; it then constructs an evaluation indicator system. The Interval Type 2 Fuzzy-Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (IT2F-DEMATEL-ANP) method is adopted to determine the weights of the indicator system, and a resilience evaluation is performed based on the Interval Type 2 Fuzzy-Prospect Theory-Technique for Order Preference by Similarity to an Ideal Solution (IT2F-PT-TOPSIS) method. Furthermore, in the case of the CTL industrial chain and supply chain of China Shenhua Energy Group Ningxia Coal Industry Co., Ltd. (CENC) (Ningxia, China), this study ranks the resilience level from 2018 to 2022 to identify the factors that have contributed to a reduction in resilience and to implement measures to enhance the resilience of the CTL industrial chain and supply chain. The results show that the level of the CTL industrial chain and supply chain resilience was lowest in 2020, while it was highest in 2021. Factors such as the degree of domestication of key technologies, the rationality of the CTL industry layout, and the stability of supply and demand chains are identified as significant determinants of resilience levels. This points the way to enhancing the resilience of the CTL industry and supply chain. Full article

Interdependent criteria play a crucial role in complex decision-making across various domains. Traditional methods often struggle to evaluate and prioritize criteria with intricate dependencies. This paper introduces a generalized method integrating the analytic network process (ANP), the decision-making trial and evaluation laboratory (DEMATEL), and the consistent fuzzy analytic hierarchy process (CFAHP) in a fuzzy environment. The Drazin inverse technique is applied to derive a fuzzy total priority matrix, and we normalize the row sum to achieve the steady-state fuzzy priorities. A numerical example in the information systems (IS) industry demonstrates the approach’s real-world applications. The proposed method derives narrower fuzzy spreads compared to the past fuzzy analytic network process (FANP) approaches, minimizing objective uncertainty. Total priority interdependent maps provide insights into complex technical and usability criteria relationships. Comparative analysis highlights innovations, including non-iterative convergence of the total priority matrix and the ability to understand interdependencies between criteria. The integration of the FANP’s network structure with the fuzzy DEMATEL’s influence analysis transcends the capabilities of either method in isolation, marking a significant methodological advancement. By addressing challenges such as parameter selection and mathematical complexity, this research offers new perspectives for future research and application in multi-attribute decision-making (MADM). Full article

The aim of this study was to study the impact of artificial intelligence (AI) on enterprises in terms of strategy, technology, business operations, and organizational management. This study used grounded theory analysis to identify the influencing factors of AI technology application maturity in Chinese enterprises. Taking Chinese film and television enterprises as an example, this study constructed an AI technology application maturity evaluation index system for enterprises based on the analytic network process (ANP) and evaluated the application maturity of AI technology in enterprises in terms of enterprise strategy, technology, business operations, and organizational management. To comprehensively evaluate and empirically analyze the application maturity of enterprise AI technology, this study calculated the index weight based on the ANP, and combined it with the fuzzy comprehensive evaluation method to construct a comprehensive evaluation model. The research results showed that intelligence strategy was the element that was believed to be most affected by the maturity of enterprise AI technology. For technology, intelligence technology and equipment were the elements that were believed to be affected the most. For business operations, smart shooting was the element that was believed to be affected the most. With respect to organizational management, corporate culture was the element that was believed to be most affected. The results showed that the proposed methods for evaluating the application maturity of enterprise AI technology are scientific and effective. The results of this study provide a reference for promoting the application of AI, implementing the intelligence transformation, and enhancing the core competitiveness of enterprises. Full article

From the perspective of firm capability, this study explores the impact of digital intelligence transformation and management innovation on the performance and sustainable development of Chinese firms. On the basis of constructing an evaluation index system of firm digital intelligence transformation and management innovation, a comprehensive evaluation model of firm digital intelligence transformation and management innovation is constructed via the analytic network process (ANP) and fuzzy comprehensive evaluation method. Taking Chinese film and television firms as an example, this study selects 160 data samples from 85 firms and constructs a structural equation model to empirically analyze the impact of digital intelligence transformation and management innovation on the performance of firms. The study results show that, in the context of digitalization and intelligence, firm digital intelligence capability and dynamic capability have a significant positive effect on firm performance. Firm digital intelligence transformation and management innovation directly impact performance and can play a role through firm digital intelligence capability and dynamic capability as intermediaries, and the chain intermediary effect of digital intelligence capability and dynamic capability is significant. The research results show that firm digital intelligence and dynamic capabilities provide a functional path for firm digital intelligence transformation and management innovation to improve performance. Moreover, the innovative application of digital intelligence technology has an important impact on the sustainable development of firms. Digital transformation and management innovation can help firms enhance their ability to manage environmental uncertainties, improve firm performance and foster the achievement of sustainable development goals. Full article

This study evaluated vegetation management (VM) strategies under electricity distribution lines (EDLs) through ecosystem service (ES) criteria. Deforestation, worsened by insufficient VM practices, poses a threat to ecosystem stability. Using a hybrid FAHP (Fuzzy Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach, ten VM strategies were assessed based on 15 ES criteria. The FAHP results identified biodiversity, timber resources, and erosion control as the most crucial criteria due to their significant weights. The TOPSIS analysis determined that VM6 (creation and restoration of scrub edges) was the most effective strategy, achieving a value of 0.744 for reducing deforestation and enhancing energy security. VM6 helps preserve forest cover and protect infrastructure by creating a “V”-shaped structures within the EDLs corridor. This study underscores the importance of ES-oriented VM strategies for sustainable vegetation management and deforestation mitigation. It also highlights the need for incorporating scientific, ES-based decision support mechanisms into VM strategy development. Future research should expand stakeholder perspectives and conduct a comprehensive assessment of ESs to ensure that VM strategies align with ecological and socio-economic sustainability. This study provides a framework for improving VM practices and offers directions for future sustainable energy management research. This study focuses exclusively on ecological criteria for evaluating VM strategies, neglecting other dimensions. Future research should use methods like ANP and fuzzy cognitive maps to explore inter-dimension relationships and their strengths. Additionally, employing SWARA, PIPRECIA, ELECTRE, and PROMETHEE for ranking VM strategies is recommended. Full article

A comprehensive evaluation system for rural building energy consumption from an innovative composite perspective was established, suitable for southwest of China. The index system was established by brainstorming and the Delphi method, the weights of the comprehensive evaluation model were calculated by the analytic network process (ANP) method, and the scoring criteria of all evaluation indexes were levelled based on fuzzy evaluation theory. The system model was verified by case analysis, in the countryside around Chengdu Second Circle. Taking into account the highest weight, lowest comprehensive score, and widest range of comprehensive scores, three key factors were identified, namely percentage of clean energy use, thermal performance of exterior walls, and implementation rate of energy-saving measures. The distribution of comprehensive indicators and evaluation factors had certain spatial distribution characteristics, and the overall spatial distribution was characteristically high in the southeast and low in the northwest. Finally, based on key factors and regional distribution characteristics, energy-saving measures are proposed from three aspects: increasing sunrooms, adding wall insulation layers, and standardizing air conditioning temperature settings. Full article

Product design is an innovative process that, through the stages of problem statement, concept, and initial and detailed design, meets the needs of customers, the requirements of companies, and their limitations. In the current process of product design and development, formulating design objectives plays a crucial role in objective setting, project implementation, product needs and requirements specification, and performing activities validation. Currently, the role of the design and development stages in the sustainability of products, identifying strategies for improving this stage is of particular significance, and paying attention to the product planning and definition process group and focusing on establishing sustainability principles in the target book and defining new attributes can be regarded as one of the sustainable product development strategies. Consequently, this research is a case study in the field of applying the sustainability principles in the target book as one of the deliverables at the stage of product planning. The present study proposes strategies towards developing the attributes of the target book as a tool for exerting sustainability pillars in the process of design and development by means of surveying automotive industry experts, applying the DEMATEL and Fuzzy ANP combined method, and evaluating and determining new attributes. Full article

The rise of wireless communication has spurred the global adoption of mobile payment services, a trend that is significantly reducing the use of cash. This shift, driven by new technologies and lifestyle changes, not only presents opportunities for businesses but also enhances consumers’ daily activities. Consumers’ and businesses’ willingness to adopt mobile payment services has increased due to factors such as easier access to new technologies, convenience, changing lifestyle choices, and economic conditions. Despite challenges such as limited access to technology, security concerns, and high transaction fees, the potential benefits of mobile payment services are promising. Therefore, this research aims to construct a suitable model for developing a mobile payment service framework that both consumers and businesses are willing to adopt. The proposed model integrates the Delphi method, interpretive structural modeling (ISM), quality function deployment (QFD), an analytic network process (ANP), and fuzzy set theory. To demonstrate the practical application of the model, a case study of developing a mobile payment service framework is presented, showcasing how the model can be used to address real-world challenges and enhance the adoption of mobile payment services. The case study results show that ease of use, system and service quality, and reliability are the most important customer requirements, and encryption, edge computing, authentication, and interoperability are the most important engineering characteristics. Full article

The complexity, increasing flow number and volumes, and challenges of last-mile logistics (LML) motivate or compel companies, authorities, and the entire community to think about ways to increase efficiency, reliability, and profits, reduce costs, reduce negative environmental impacts, etc. These objectives can be met by applying Industry 4.0 (I4.0) technologies, but the key question is which one. To solve this task, this paper used an innovative method that combines the fuzzy analytic network process (fuzzy ANP) and the fuzzy axial-distance-based aggregated measurement (fuzzy ADAM) method. The first was used for determining criteria weights and the second for selecting the best variant. The best solution is e/m-marketplaces, followed by cloud-computing-supported management and control systems and blockchain. These results indicate that widely adopted and implemented technologies are suitable for last-mile logistics. Newer technologies already producing significant results have serious potential for further development in this area. The main novelties and contributions of this paper are the definition of a new methodology based on multi-criteria decision-making (MCDM) methods, as well as its application for ranking I4.0 technologies for LML. Full article

This study proposes an approach for simultaneously treating fuzziness and randomness when conducting safety risk assessments of nuclear power plant building projects (NPPBPs). First, the interval type-2 fuzzy set (IT2FS) and analytic network process (ANP) were employed to establish an IT2FS-ANP method for modifying the solution for the weight vector and determining the mutual relationships between the assessment indexes and their weights. Second, the IT2FS and cloud model (CM) were used to establish the IT2FS-CM method to modify the solution for the expectation value. Third, the IT2FS-ANP and IT2FS-CM methods were combined to establish a model for ranking the safety risks and determining the overall safety risk level. Finally, the approach was applied to an NPPBP in northeast China to validate its applicability. Full article

Making decisions and building strategies to enhance the supply chain are currently essential if companies want to keep up with modern advances and compete in both the local and global markets. However, the coronavirus pandemic heightened the necessity for decision making and the adoption of strategies for supply chain improvement and transformation to effectively deal with crises and ongoing change. This paper introduces a framework for recovery strategies to characterize the correlation at various stages among the key concerns of the supply chain because of COVID-19, recovery decisions, the areas of development, the strategic recovery plan, and the objectives of the recovery strategies to restore the supply chain (SC). This study used a combination of quantitative and qualitative techniques to identify possible areas for supply chain improvement and rank viable solutions. A combined fuzzy ANP–fuzzy TOPSIS method is proposed to prioritize and rank the areas of improvement. The results indicate that digitization and the utilization of emerging technology play critical roles in supply-chain recovery from disruptions and different current and future SC changes. Full article

The integration of green design into building construction is a necessary process in today’s world to address environmental issues and achieve sustainable development. However, when evaluating green building design schemes, various factors are intertwined with a high degree of complexity and uncertainty. To realise rational decision-making about green building design schemes, this paper first adopts the mixed techniques of triangular fuzzy numbers, quality function deployment, and Best–Worst Method. It aims to analyse the complex factor relationship between customer needs and green building design technical features and to solve the optimal green building design index weight allocation. Next, a hybrid fuzzy multi-criteria decision-making (MCDM) method integrating triangular fuzzy numbers, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, and Grey Correlation (GC) are proposed to evaluate green building design scheme performance. Finally, an example of a green design project for a hotel building is selected for application validation and analysis in comparison with the existing Complex Proportional Assessment, VlseKriterijuska Optimizacija I Komoromisno Resenje, and DEMATEL-ANP methods. These analyses demonstrate the stability and validity of the results, as well as the rationality and practicability of the proposed triangular fuzzy QFD–MCDM method. This research is a guide to the problem of evaluating green building design schemes. Full article