Multi-attributive Border Approximation Area Comparison Research Articles

An integrated multicriteria decision making framework for the selection of waste cement dust filled automotive brake friction composites

This work discusses selecting optimal brake friction composite alternatives based on an integrated MABAC (multi-attributive border approximation area comparison) and AHP (analytic hierarchy process) approach. Therefore, non-asbestos automotive brake friction composites containing varying proportions of cement dust (50 to 0 wt%) and barium sulfate (0 to 50 wt%) were developed and tribo-evaluated on a Krauss machine following European regulations. Composite made up of 30 wt% cement dust and 20 wt% barium sulfate had the highest friction coefficient (0.361), lowest variability coefficient (0.598), and maximum recovery (123.27%). The composite with the least fading (15.36%) included 50 wt% cement dust, whereas the composite with the lowest wear (9.10 g) and the least frictional fluctuations (0.271) contained 50 wt% barium sulfate. By AHP, the friction coefficient (0.1989), fade (0.1696), recovery (0.1551), and wear (0.1412) were selected as the essential criteria in the performance assessment. Based on the MABAC ranking evaluation, the composite comprises 20 wt% barium sulfate and 30 wt% cement dust has the best tribological profile, whereas the composites of solely cement dust or barium sulfate have the poorest tribological profile. The acquired ranking results were confirmed using other decision-making models and subjected to sensitivity analysis to demonstrate their robustness.

MABAC-based evaluation of multimedia technology application effect in film and television post-production

Computer multimedia technology first appeared in the late 1980s, which is a functional upgrade based on the development of digital technology. It can achieve functions such as information collection, processing, and storage. Multimedia technology has received widespread attention in the entire computer field and has become a popular technology. Against the backdrop of continuous technological development, various electronic products are presented to people, bringing convenience to their lives. At the same time, they also play a huge role in the work of some industries. The application of multimedia technology, advanced editing software, and digital equipment in the production of video works can present good results and showcase excellent film and television works for people. The application effect evaluation of multimedia technology in the film and television post-production is frequently viewed as a multi-attribute group decision-making (MAGDM) issue. The maximizing deviation method was used to obtain the weight information under intuitionistic fuzzy sets (IFSs). Depending on the MABAC (multi-attributive border approximation area comparison) method and IFSs, this paper design the intuitionistic fuzzy MABAC (IF-MABAC) method to assess the application effect evaluation of multimedia technology in the film and television post-production. Eventually, an example about application effect evaluation of multimedia technology in the film and television post-production and some comparative analysis have been employed to verify the superiority of the designed IF-MABAC method.

Contamination control in the oil and gas industries using industrial separation technologies: A sustainability and safety-oriented DSS under Pythagorean fuzzy environment

ABSTRACT The challenges related to the sustainability and safety policies to use the technologies for separating industrial contaminants in the oil and gas industry necessitate an investigation based on these policies. The criteria are in four economic, technical, social, and environmental aspects (as sustainability principles), and three applicability, functionality, and integrity aspects (as safety principles). The research aims at extending a novel decision support system (DSS) by integrating MEREC (method based on the removal effects of criteria) and MABAC (multi-attributive border approximation area comparison) methods under the Pythagorean fuzzy set. Its notable advantages are that renders a stronger expression of uncertainty and the decision-making process is more closely managed. Also, it allows the decision-maker (DM) to evaluate in a wider area and avoid data and conflict among the decision-making team. The industrial separation technologies prioritization is implemented with the DSS. These technologies have been taken into account for contamination control in the sector of Iran’s natural gas processing. The results of the prioritization are: High-efficiency liquid–gas coalescer technology, mesh pad technology, filter separator technology, cyclonic separator technology, vane pack technology, two-phase separator technology, and supersonic separator technology. The high-efficiency liquid–gas coalescer technology is selected as the preferable alternative.

WITHDRAWN: Sustainable circular supplier selection for textile manufacturing industries in India: An integrated WINGS-MABAC approach

The significant quantity of waste produced by the textile industry has recently sparked an increase in the adoption of Circular Economy (CE). To aim towards CE, companies should focus on selecting suppliers who share certain key characteristics, such as being compliant with the CE standards, recycling used resources to reduce waste, minimal use of water & energy. Till date, very few studies have managed to cover the in-depth analysis of suppliers on the basis of circularity and sustainability aspects. The criteria addressed in this study have been identified through thorough literature review and discussions with the experts. This paper addresses this problem with the aid of multi-criteria decision-making (MCDM) framework for sustainable circular supplier selection (SCSS) in the Indian textile industry. This study applies Weighted Influence Non-linear Gauge System (WINGS) - Multi-Attributive Border Approximation Area Comparison (MABAC) approach to estimate the importance of different criteria to select the best performing supplier of recycled cotton yarn for an Indian textile industry. WINGS is used to analyse the different criteria for evaluating suppliers in textile industry, while MABAC is used to select the most suitable sustainable circular supplier. Our results suggest that sustainable circular suppliers should be evaluated mainly on the basis of factors like whether or not the supplier is willing to collaborate, robustness, green certifications and the recycling capability of the suppliers. The proposed approach and decision-making model can help the managers of the textile industry to choose more sustainable suppliers, respond to fast fashion and maintain the competitive standard in the market. An illustrative application of the proposed framework is undertaken in an Indian textile micro, small and medium enterprise (MSME).

Optimizing Cross-Dock Terminal Location Selection: A Multi-Step Approach Based on CI-DEA–IDOCRIW–MABAC for Enhanced Supply Chain Efficiency—A Case Study

Thedistribution of products stands out as one of the pivotal activities for logistics companies in recent years, particularly in the aftermath of the COVID-19 pandemic and other geopolitical events. Intense competition compels companies to efficiently execute their logistical processes, with cross-docking emerging as a frequently applied solution. However, the location of cross-dock terminals in urban areas remains a problem insufficiently addressed in the literature, with a dearth of studies and models tackling this issue. This paper introduces a novel and innovative model for locating cross-dock terminals based on the CI-DEA–IDOCRIW–MABAC (Composite Indicators–Data Envelopment Analysis-Integrated Determination of Objective Criteria Weights–Multi-Attributive Border Approximation Area Comparison) methods. In the process of defining input indicators, the following three sources were utilized: relevant literature, practical insights from logistics experts, and the knowledge and experience of the authors. Eight inputs and three outputs were considered (the number of users in the observed channel; the area served by the channel; the average distance a vehicle travels in one delivery; the required number of vehicles; labor availability; competition; construction, and expansion possibilities; proximity to the main infrastructure and traffic facilities; the average number of deliveries; average delivered quantity; and service level). The model underwent testing in a case study analyzing nine distribution channels (areas within the observed urban zone). The results indicated that alternative A4 (in the southwest area) ranked the highest since it was the best-ranked in accordance with the most important criteria, suggesting that the terminal is best located in the southwest zone. The accuracy of the results was confirmed by company management. By developing a completely new model and addressing the identified gap in the literature, this paper provides unequivocal scientific contributions.

A hybrid heterogeneous framework for medical waste disposal evaluation by fusing group BWM and regret-rejoice MABAC

This article attempts to develop a hybrid heterogeneous framework to evaluate the disposal modes for emergency medical waste (EMW) by fusing GBWM (group best-worst method), RT (regret theory), and MABAC (multi-attributive border approximation area comparison). This hybrid framework tries to address three key challenges: (i) determining criteria weights, (ii) computing the regret-rejoice evaluation matrix, and (iii) identifying the optimal alternative. To address the first challenge, this paper innovates an innovative interval-valued intuitionistic fuzzy (IVIF) GBWM, which considers multiplicatively consistent IVIF preference relation, to efficiently determine global criteria weights (GCWs). For the second challenge, RT is incorporated to compute the regret-rejoice evaluation matrix using experts' heterogeneous evaluations which consist of intervals, triangular fuzzy numbers, hesitant fuzzy linguistic term sets and IVIF values. Regarding the third challenge, MABAC is applied to sort alternatives based on the obtained regret-rejoice evaluation matrix. Afterwards, the validity of the hybrid framework is verified by an illustrative example, and its advantages are demonstrated with some worthy sensitivity and comparative analyses. Some innovations of the proposed framework are highlighted below: (i) The IVIF GBWM streamlines calculation load, since it derives GCWs by solving the group weight assignment model only once; (ii) The introduction of RT into MABAC assists decision-makers in mitigating regret psychology, enhancing the quality of decision outcomes; (iii) The proposed framework’s practicality is enhanced by leveraging heterogeneous evaluations which capture the inherent complexities of actual decision-making problems.

Enhancing efficiency in photo chemical machining: a multivariate decision-making approach

Non-Traditional Machining (NTM) outperforms traditional processes by offering superior geometric and dimensional accuracy, along with a better surface finish. Photo Chemical Machining (PCM) represents one such NTM process, using chemical etching for material removal. PCM finds substantial application in the creation of microchannels in pharmaceutical, chemical and energy industries. Several input parameters—such as etchant concentration, etching time and etchant temperature—profoundly influence the machining’s quality and efficiency. Therefore, the optimization of these parameters is crucial. This study presents a comparative analysis of five Multiple Criteria Decision Making (MCDM) techniques—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Multi-Objective Optimization on the basis of Ratio Analysis (MOORA), Additive Ratio Assessment (ARAS), Weighted aggregated sum product assessment method (WASPAS) and Multi-Attributive Border Approximation Area Comparison Method (MABAC)—for the optimization of the PCM process. Key performance metrics considered are Material Removal Rate (MRR), Surface Roughness (SR), Undercut (Uc) and etch factor (EF). The weights of these criteria were calculated using the Criterion-Induced Aggregation Technique (CRITIC) and was compared with other popular methods like MEREC, Entropy and equal weights. MRR and EF are seen as beneficial criteria, while SR and Uc are perceived as cost criteria. Optimum process parameters were identified as 850 g/L etchant concentration, 40 min etching time and 70°C etchant temperature. Two of the three employed MCDM techniques agreed on these optimal parameters, reinforcing the findings. Furthermore, a strong correlation was observed amongst the employed MCDM techniques, further validating the results.

An efficient Model for Selection of Unmanned Aerial Vehicles designed for Precision Agriculture

Precision agriculture (PA) utilizing unmanned aerial vehicles (UAVs) has supplanted labor-intensive and time-consuming conventional agricultural methods in recent times. This is because of its great economic benefits, as it possesses many advantages. It's fascinating to see how drones are being increasingly used in agriculture due to the numerous benefits they offer. However, it's important to evaluate their performance and determine the most effective criteria to ensure their optimal use. To make the most effective use of drones in agriculture, we need to consider multiple criteria when making decisions about their performance. The suggested model is constructed utilizing neutrosophic sets to effectively handle uncertainty and address multi-criteria decision-making (MCDM) situations with several competing criteria and options. The proposed model integrates Multi-Attributive Border Approximation Area Comparison (MABAC), and the entropy method for evaluating the performance of UAVs in PA based on diverse criteria and their importance, along with single-valued neutrosophic sets (SVNSs). The entropy method is used for calculating the weight of criteria, and the MABAC method is used for ranking alternatives. An experimental case study has been established for choosing the best UAV for precision agriculture.

Interval-valued fermatean fuzzy based risk assessment for self-driving vehicles

The decision-making(DM) processes used by autonomous vehicle driving systems are separate from those of the users, allowing them to oversee and regulate the operations of the cars in expected and unforeseen circumstances. Although there are several advantages to using this technology, such as fewer accidents caused by human error and more efficient energy utilization, it is also evident that there are some risks involved. Hence, developing a risk assessment application for these systems will be advantageous given the hazards associated with autonomous cars and driving systems that must be tested and addressed. In this study, a new integrated FF-based MCDM methodology combining the Analytic Hierarchy Process(AHP), Technique for Order Preference by Similarity to Ideal Solution(TOPSIS), and Multi-Attributive Border Approximation Area Comparison (MABAC) methods is proposed as a new security model that will help decision-makers address the physical design and attack risks of autonomous vehicles, estimate their uncertainty, and control cyber risks Interval-valued Fuzzy Fermatean sets ten possibilities for autonomous vehicle driving systems assessed in the application based on six main criteria and fifteen sub-criteria. Comparative and sensitivity studies have also been used to demonstrate the adaptability, validity, and verification of the suggested approach and the sensitivity of the decisions made. Possible implications from a theoretical, managerial, and policy framework have been examined based on the application findings and studies that have been done.

Effective hydropower renewable energy source selection using fuzzy neutrosophic boundary approximate area

Small hydropower plants in rural areas are contributing to marginal economic growth and social progress, but their social sustainability assessment is under-studied. Previous studies have shown that no single renewable energy source (RES) can fully meet all sustainability criteria, despite their focus on single-user systems. Scaled renewable energy systems have varying impacts across different systems, involving technical, environmental, social, and economic aspects. This paper proposes a Triangular Fuzzy Neutrosophic Numbers (TFNNs) as an extension of the multi-attributive border approximation area comparison (MABAC) method for hybrid multi-criteria decision-making (MCDM). The proposed method is utilized to assess the selection of hydropower as the most efficient and sustainable renewable energy source for society. Pairwise comparison matrices were used to determine priority vectors and weighted averages of indicators for seven criteria. The evaluation framework analyzed five key dimensions of hydropower plants. The most stable renewable energy source, pumped storage hydropower (60.78%), was found to be followed by run-of-river hydropower (56.39%), impoundment hydropower (50.03%), storage hydropower (39.78%), and offshore hydropower (07.95%). The study offers valuable insights for policymakers and implementer on sustainable electricity solutions for hydropower. Pumped storage hydropower (PSH) improves facility efficiency by ensuring optimal operation of coal and nuclear generators without energy loss. The system can provide a stable and reliable power storage solution for renewable energy sources like wind and solar.

Supplier selection of companies providing micro mobility service under type-2 neutrosophic number based decision making model

Environmental approaches play an active role in the production platform as well as in the supply chain. Studies that deal with supplier selection problems in the supply chain with a green focus have recently intensified. In this research, the supplier selection problem of companies providing “last mile” service, which is seen as the last step of transportation, is handled with a green focus. The supplier selection problem of these companies is differentiated according to strategic and non-strategic product groups. In this study, a green-oriented supplier selection proposal is presented for both the strategic product group and the non-strategic product group. The supplier selection problem is accepted as a multi criteria decision making problem (MCDM). Thus, the type-2 neutrosophic numbers (T2NNs) - based CRiteria Importance Through Intercriteria Correlation (CRITIC) – based Multi-Attributive Border Approximation Area Comparison (MABAC) hybrid model is applied to evaluate the green-oriented supplier. The motivation of the study is to determine the best alternative supplier type for strategic and non-strategic products groups. In this context, two cases are created, ten criteria are selected, and three supplier types are determined. Supplier types are as follows: (i) Classical suppliers, (ii) Hybrid-Classical to green centric suppliers, and (iii) Start-Ups & green centric suppliers. To devise a solution for addressing the research problem, the selection of the optimal green supplier type was accomplished through a recommended T2NN-CRITIC-MABAC hybrid model. Accordingly, for both strategic and non-strategic product groups, micro-mobility service providers identified Hybrid-Classical to Green Centric Suppliers as the most suitable green supplier type. In addition, the findings are strengthened by creating twenty-two sensitivity analysis scenarios. In conclusion, the T2NN-CRITIC-MABAC hybrid method introduced in this study represents a methodologically diverse, fuzzy logic-based approach with practical implications for supplier selection in the micro mobility services sector. Its application and empirical testing contribute to the literature and provide valuable insights for decision-makers in the industry.

Decision Support System for Performance Assessment of Honoray Personnel Applying MABAC, MOORA, and ARAS Method with a Combination of ROC Weighthing

MABAC (Multi-Attributive Border Approximation area Comparison), ARAS (Additive Ratio Assessment), and MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) are decision support system methods employed for evaluating the performance of honorary staff. MABAC utilizes a multi-attribute border approximation area approach to measure the relative performance of honorary staff. ARAS assigns weights to competing attributes and produces assessment ratio values aiding in decision-making. Meanwhile, MOORA focuses on multi-objective optimization by considering ratio analysis. The combination of these three methods provides a holistic and comprehensive framework for assessing the performance of honorary staff, enabling decision-makers to effectively evaluate their contributions and achievements based on predefined criteria. This approach allows for the determination of relative rankings and the selection of honorary staff that best align with organizational needs

Decision Support System Analysis of School Promotion Media Selection using MABAC, OCRA And CODAS Methods

School promotion is an activity to communicate educational products to consumers or prospective students. Promotional activities require strategic policies in order to maximize promotional results, therefore analysis of the selection of appropriate promotional media needs to be done. Multi-Attributive Border Approximation area Comparison, Operational Competitiveness Rating Analysis, COmbinative Distance-based Assessment in decision support system with case study at SMK Airlangga Balikpapan. MABAC, OCRA and CODAS are used in the calculation process that produces output in the form of promotional media ranking to be recommended to the school promotion team as a consideration for selecting the right promotional media. Alternative promotional media used in this research are brochures, posters, billboards, banners and newspaper advertisements. Based on the results of the research, the MABAC, OCRA and CODAS methods can be applied to the school promotion media selection decision support system and can produce output in the form of a priority ranking of school promotion media

A novel MABAC approach for multi-attribute group decision-making with single-valued neutrosophic sets: An application in assessing microfinance group lending performance

In the 40 years of global microcredit practice, loan technology has played a positive role in microcredit as one of the most important supporting elements. The development and evolution of microcredit institution lending technology is the result of comprehensive consideration of specific regional economic, social, cultural, and geographical factors. In the context of the diversified trend of microcredit technology, choosing loan technology reasonably, exploring flexible guarantee conditions, and innovating diversified loan technology combinations will become practical problems faced by microcredit institutions, and also the direction of theoretical research. The timely innovation of group loan technology in microcredit has practical value and theoretical significance for promoting the innovation of financial agricultural products in the implementation of China’s rural revitalization strategy, as well as bridging the theoretical controversy of microcredit loan technology. The performance evaluation of microfinance groups lending is a MAGDM issues. In this paper, the distances measures of single-valued neutrosophic sets (SVNSs) and maximizing deviation method (MDM) is used to obtain the attribute weight values. Based on the classical Multi-Attributive Border Approximation area Comparison (MABAC) method, the single-valued neutrosophic numbers MABAC (SVNN-MABAC) method is constructed for MAGDM under SVNSs. Finally, an example for performance evaluation of microfinance groups lending and some comparative decision analysis are constructed to verify the SVNN-MABAC model.

Mapping the Evolution of Multi-Attributive Border Approximation Area Comparison Method: A Bibliometric Analysis

This paper presents a comprehensive bibliometric analysis of Multi-Attributive Border Approximation Area Comparison (MABAC) method using the Biblioshiny application of the bibliometrix package, R program and VOSviewer tools to provide a holistic view of the research landscape by identifying its evolution, major contributors and most influential research areas. The study, analyzing 264 articles from the Scopus database (January 2015 to September 2023), reveals China as the leading contributor, with India spearheading international collaboration. The most impactful publication, "The selection of transport and handling resources in logistics centres using MABAC," by Pamučar and Ćirović [2], boasts 537 citations. Notably, the "University of Defence in Belgrade" is a prominent institution in this domain. "Pamučar D" emerges as the most cited author. Key terms include "MABAC," "MABAC method," and "MCDM," commonly associated with MABAC method. The top three cited journals are "Expert Systems with Applications," "Decision Making: Applications in Management And Engineering," and "Symmetry." The study provides valuable insights for researchers, practitioners, and decision-makers interested in MABAC's applications and future developments in MCDM, contributing to ongoing discussions about its relevance.

The SMAA-MABAC approach for healthcare supplier selection in belief distribution environment with uncertainties

Supplier selection is critical to the healthcare industry, especially in emergencies. Accurate and timely supply of healthcare resources can reduce economic cost and ensure the safety of people’s lives. However, the healthcare supplier market is enormous and complex; making accurate evaluations of different suppliers and helping managers choose the most suitable one when considering many factors is becoming an important task. Many multicriteria decision-making (MCDM) methods have been applied to supplier selection in existing literature. However, the research on healthcare supplier selection still needs to be completed. In this paper, to deal with healthcare supplier selection problems when there is no sufficient time and information to decide with uncertainty, the stochastic multicriteria acceptability analysis (SMAA) method and multi-attributive border approximation area comparison (MABAC) method are first combined by taking both the advantages of SMAA and MABAC methods when the assessments are expressed by belief distributions (BDs). In the SMAA-MABAC method, the global ignorance in BDs and the uncertain criteria weights are considered by judging the feasible space to derive the final rank of healthcare suppliers with the most possible. The more straightforward calculation process of SMAA-MABAC makes it faster to make an accurate choice among various suppliers. Moreover, it is flexible to generate different recommended suggestions when diverse preference information is added in SMAA-MABAC. Finally, a case study of healthcare supplier selection is examined for managers based on distributed reviews, and targeted selection advice is given concerning different demands. Besides, the sensitive analysis is provided to better understand the influence of the criteria weights on the proposed model. The results of the comparative analysis also show the effectiveness and rationality of the proposed method.

Exploring decision-making techniques for evaluation and benchmarking of energy system integration frameworks for achieving a sustainable energy future

Energy Systems Integration (ESI) involves coordinating and planning energy systems to provide reliable and affordable energy services while minimizing environmental harm. It optimizes interactions among different energy sources to achieve sustainability goals and promotes efficient resource usage. However, evaluating and benchmarking ESI frameworks to select the most suitable and transparent ones is a complex Multi-Criteria Decision-Making (MCDM) problem. This complexity arises from trade-offs, conflicts, and importance considerations of the six ESI evaluation characteristics: Multidimensional, Multivectoral, Systemic, Futuristic, Systematic, and Applied. Hence, this study aims to address this complexity by integrating Fuzzy-Weighted Zero-Inconsistency (FWZIC) and Multi-Attributive Border Approximation Area Comparison (MABAC). The proposed methodology consists of two phases. Firstly, the development of a Dynamic Decision Matrix (DDM) to handle 26 ESI frameworks as alternatives and the six ESI characteristics criteria. Secondly, the integration of mathematical processes is formulated based on the FWZIC-MABAC methods. Using the FWZIC technique, the ESI evaluation criteria were weighted based on the preferences of twelve experts. ESI-C2 (Multivectoral) and ESI-C1 (Multidimensional) criteria received the highest weights of 0.195 and 0.190, respectively, while the ESI-C5 (Systematic) criterion received the lowest weight of 0.110. The remaining criteria, namely ESI-C3 (Systemic), ESI-C6 (Applied), and ESI-C4 (Futuristic) obtained weights of 0.189, 0.168, and 0.147, respectively. The MABAC benchmarking results showed that A11 (Energy Security) and A15 (Energy Security under decarbonization) ranked first with the highest score value of 0.28081 for both. Conversely, A19 (EJM) had the lowest score value of −0.17022. The systematic rank and sensitivity analysis assessments were conducted to verify the efficiency of the proposed methodology. We benchmarked the proposed methodology against three other benchmark studies and achieved a score of 100 % across three key perspectives. This methodology offers valuable support in making informed and sustainable decisions in the energy sector.

Site selection decision for biomass cogeneration projects from a sustainable perspective: A case study of China

Biomass energy has made significant contributions to energy demand and environmental protection. The purpose of this study is to establish a new integrated method adapted to the site selection of biomass cogeneration projects. The highlight lies in the integration of Multiple Criterion Decision Making methods with Geographic Information System at different stages. This study takes Henan Province as an example to introduce the application of this model. Stage I preliminary screening stage: use Geographic Information System and Fuzzy Best Worst Method to classify the suitability level of project site selection within the research area. Identify alternative solutions in areas with high suitability and large patch area. Stage II selection stage: Calculate the indicator weights using Criteria Importance Through Intercriteria Correlation method first; Then use the Multi-attributive Border Approximation Area Comparison method to select the optimal factory site. Using geographic information system technology, the factory is selected to be built in an area with a suitable value greater than 7 in Xiangcheng County, Zhoukou City. Finally, the obstacle model diagnoses the direction of optimizing the location environment. This study provides a theoretical reference for the new construction, renovation and expansion of biomass cogeneration projects.

A Neutrosophic Multi-Criteria Model for Evaluating Sustainable Soil Enhancement Methods and their Cost Implications in Construction

This paper provides a comprehensive overview of the application of life cycle assessment (LCA) to promote sustainable soil practices in construction foundation projects. The aim is to evaluate the environmental impact and long-term sustainability of soil-related activities in construction through the lens of LCA. This assessment encompasses a wide array of factors, including soil quality, erosion control, contaminant remediation, soil stability, conservation, drainage management, and compliance with regulatory standards. To address this multifaceted evaluation, we employ a multi-criteria decision-making (MCDM) model, specifically introducing the Multi-Attributive Border Approximation Area Comparison (MABAC) method. This MCDM technique is utilized to appraise the sustainability of soil practices and is integrated with a neutrosophic set to handle imprecise information. Our study incorporates nine criteria and eight alternative methods. Through the application of LCA, construction professionals can uncover strategies to minimize the carbon footprint of their projects, optimize soil utilization, and enhance the long-term resilience of their structures. Achieving a comprehensive LCA tailored to the specific requirements of each project and local regulations necessitates close collaboration between soil engineers, environmental experts, and construction practitioners.

Two-stage site selection of hydrogen refueling stations coupled with gas stations considering cooperative effects based on the CRITIC-ITFAHP-MABAC method: A case study in Beijing

Powering hydrogen-fueled vehicles (HFVs) through hydrogen electrolysis using excess sustainable energy is an effective way to move towards sustainable development. Hydrogen refueling stations (HRSs) coupled with gas stations (GSs) can effectively integrate and utilize the resources in existing GSs, improve operational efficiency, and promote the cooperative income of the two. Aiming at the lack of cooperative effects between gas and hydrogen considered in the current site selection process for HRSs, a general criterion establishment process with refined measurement system are proposed to determine a more comprehensive criterion system, including the cooperative criteria and the precise calculation formula of each criterion. Based on these, a new two-stage site selection framework for HRSs is established. The first stage offers eligible alternatives through veto criteria. Then in the second stage, the Criteria Importance Through Intercriteria Correlation (CRITIC) and Improved Triangular Fuzzy Analytic Hierarchy Process (ITFAHP) methods are used to determine the objective weights and subjective weights of the criteria, and the results are combined according to the minimum deviation estimation (MDE). The rankings of alternatives are finally determined through the Multi-Attributive Border Approximation Area Comparison (MABAC) method. Three scenarios are proposed for further analysis in the case study of Beijing, China. The results show that the two-stage site selection framework with new criterion system makes the evaluation results more differentiated. When the importance coefficient of subjective weights reflecting the importance of the criterion in practice changes from 0 to 1, the score increase of the best alternative A5 (Zhoujiaxiangbei) is 49.14% higher than that of the second-ranked alternative, indicating that this alternative is more in line with people's perception of a good selection. The analysis results also further verify the rationality and robustness of the decision-making framework.