Multi-attributive Border Approximation Area Comparison Method Research Articles

Comparison Of G-7 Countries' Macroeconomic Performance with SD and MABAC Methods

Countries determine their economic policies according to macroeconomic performance criteria. Macroeconomic performance criteria provide basic information on the level of development of countries. A reduction in unemployment, price stability and a balanced budget are important for achieving economic growth and competitiveness. The aim of this study is to analyse the macroeconomic performance of the G7 (Germany, the United States, the United Kingdom, Italy, France, Japan and Canada), a union of the seven countries with the highest level of development in the world, between 2018 and 2022. . In the study, macroeconomic criteria (unemployment, inflation, external balance, and growth), which are called "magic diamonds" by OECD (Organization for Economic Cooperation and Development), were applied using SD (Standard Deviation) and MABAC (Multi-Attributive Border Approximation Area Comparison) methods. According to the results of the SD method, the inflation criterion has the greatest impact on macroeconomic performance in 2018 and 2019, the unemployment criterion in 2020 and 2022, and the growth criterion in 2021. According to the results of the MABAC method, Germany had the highest macroeconomic performance in 2020, and Japan had the highest macroeconomic performance in the other analyzed years.

Analysis of Trade Competitiveness of the World s Leading Textiles Exporters by Hybrid MCDM Methods

Purpose –This paper demonstrates the application of the IDOCRIW-based MABAC and MAIRCA methods in the evaluation of the trade competitiveness of the top fifteen textiles exporters in the world. Design/methodology/approach –The trade competitiveness index was used for assessing the trade competitiveness of exporters in the textile industry. The IDOCRIW method was used to obtain the weight of criteria. The analysis of the trade competitiveness of exporters was carried out using the new multi-criteria methods, namely the MABAC (Multi-Attributive Border Approximation area Comparison) and the MAIRCA (Multi-Atributive Ideal-Real Comparative Analysis). Findings –According to the results obtained by the IDOCRIW method, share in the world market (SWM) and net exports (NEX) were determined as the most and least important criteria with weight values of 0,3297 and 0,0816, respectively. After determining the criteria weight, the alternatives were ranked using the MABAC and MAIRCA methods. The results for both methods indicate that China, Italy, Luxembourg, Belgium, and Spain have the highest trade competitiveness, while Croatia, Ireland, the Republic of Cyprus, Malta, and Mexico have the lowest trade competitiveness in the textile industry. The findings demonstrated that MABAC and MAIRCA provided consistent solutions for ranking the alternatives. Additionally, the consistency and robustness of the results were tested using two different scenarios. The overall results revealed that China and Italy have the best trade competitiveness in the textile industry. Discussion –As expected, China and the European Unioun (EU) countries have the highest trade competitiveness in the world’s textile industry. It can also be stated the textile industry is strategic sector for both the EU countries and China.

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.

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.

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

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.

Assessment of inorganic solid waste management techniques using full consistency and extended MABAC method.

Population and industrial growth have spiked product consumption, which in turn have caused an abrupt rise in municipal solid waste (MSW) production. Due to the lack of resources allocated to waste management, municipal inorganic solid waste (ISW) has increased exponentially, posing a significant strain on the environment and health. To mitigate these issues, sustainable waste management strategies need to be implemented to reduce environmental impacts and improve waste collection and disposal efficiency. The objective of our work was to analyse and identify the most effective techniques for disposing of ISW in India by employing multi-criteria decision-making (MCDM). This technique entails selecting the most suitable alternative based on a variety of competing and interactive criteria. A fusion decision model named the FULL COnsistency Method (FUCOM) and Multi-Attributive Border Approximation area Comparison (MABAC) based on the interval-valued q-rung orthopair fuzzy (IV q-ROF) was developed. Finally, a comparative analysis was performed to demonstrate the system's robustness.

Evaluating the Popularity of Programming Languages in Indonesia using the MABAC Method

<span lang="EN">In today's fast-paced digital era, the selection of a programming language plays a crucial role in the success of software development projects. This research aims to create an index of popularity for programming languages using the multi-attributive border approximation area comparison (MABAC) method. The study considers four data sources, including Jobstreet.Com, LinkedIn.Com, Google Trends, and Tiobe.com, to obtain the necessary information for evaluating the popularity of programming languages in Indonesia. The data range for this study is from May 1, 2020, until April 31, 2021. The results of the study indicate that the top ten programming languages in terms of popularity in Indonesia are Java, SQL, php, JavaScript, C, C++, python, C#, Visual Basic, and Assembly. The index can serve as a useful guide for strategic decision-making regarding the selection of programming languages for addressing the needs of the information technology market in Indonesia. The study's findings can be useful for software developers, IT professionals, and decision-makers in organizations who need to select a programming language for their software projects in Indonesia. The MABAC method used in this study can also be applied to other contexts for evaluating the popularity of programming languages.</span>

Integrating Fuzzy Rough Sets with LMAW and MABAC for Green Supplier Selection in Agribusiness

The evolving customer demands have significantly influenced the operational landscape of agricultural companies, including the transformation of their supply chains. As a response, many organizations are increasingly adopting green supply chain practices. This paper focuses on the initial step of selecting a green supplier, using the case study of the Semberka Company. The objective is to align the company with customer requirements and market trends. Expert decision making, grounded in linguistic values, was employed to facilitate the transformation of these values into fuzzy numbers and subsequently derive rough number boundaries. Ten economic-environmental criteria were identified, and six suppliers were evaluated against these criteria. The fuzzy rough LMAW (Logarithm Methodology of Additive Weights) method was employed to determine the criteria weights, with emphasis placed on the quality criterion. The fuzzy rough MABAC (Multi-Attributive Border Approximation Area Comparison) method was then utilized to rank the suppliers and identify the top performer. The validity of the results was established through validation techniques and sensitivity analysis. This research contributes a novel approach to green supplier selection, employing the powerful tool of fuzzy rough sets. The flexible nature of this approach suggests its potential application in future investigations. The limitation of this study is more complicated calculations for the decision maker. However, this approach is adapted to human thinking and minimizes ambiguity and uncertainty in decision making, and in future research, it is necessary to combine this approach with other methods of multi-criteria analysis.

A comparative analysis of Multi-Attributive Border Approximation Area Comparison (MABAC) model for healthcare supplier selection in fuzzy environments

Access to high-quality and affordable healthcare services is necessary for people worldwide. Achieving this goal requires healthcare providers to procure the best available equipment and pharmaceutical items at the lowest possible cost. Hence, proper supplier selection is crucial for all healthcare organizations to ensure the availability of the right products in the right quantity at the right time and minimum cost. This paper employs a multi-criteria decision making (MCDM) tool, i.e., Multi-Attributive Border Approximation Area Comparison (MABAC), in seven different fuzzy environments to solve a healthcare supplier selection problem. Fuzzy MABAC, intuitionistic fuzzy MABAC, Pythagorean fuzzy MABAC, neutrosophic fuzzy MABAC, hesitant fuzzy MABAC, spherical fuzzy MABAC, and Fermatean fuzzy MABAC are considered here to search for the most appropriate healthcare supplier while simultaneously optimizing conflicting criteria. We show that all the fuzzy-integrated MABAC methods lead to the same set of the best and worst healthcare suppliers regardless of the fuzzy environment employed. Furthermore, these fuzzy MABAC methods can efficiently deal with varying decision makers’ judgments and uncertainty associated with qualitative criteria, such as quality, responsiveness, reliability, etc., that form a major component of any healthcare supplier selection problem

A comprehensive mortise and tenon structure selection method based on Pugh's controlled convergence and rough Z-number MABAC method.

Mortise and tenon joints are widely used in the building and furniture industries because of their excellent mechanical and eco-friendly properties. In real-life cases, there are usually many available alternative structures for a joint area, it is a challenge to select a proper structure from massively available alternatives. This paper aims to select a proper multiple attribute decision-making method based on massive alternatives and unreliable, uncertain and subjective information. Pugh's controlled convergence, rough number, Z-number, consistency theory and Shannon entropy are integrated and proposed an improved rough Z-number Multi-Attributive Border Approximation Area Comparison (MABAC) method. Firstly, Pugh's controlled convergence is a selection method, simple and rapid, presented in the first phase to eliminate most of the alternatives. In the second phase, an integrated method is proposed. The consistency theory, distance measurement and the Z-number are initially aggregated to calculate the expert weight. The entropy method is then presented to determine the criteria weight. The alternatives are then ranked and the optimal mortise and tenon joint is selected based on the rough Z-number MABAC method. A real-life case is presented, and the proposed method is implemented in the joint of a bucket cabinet. Finally, the efficiency and effectiveness of the proposed method are proved by the case, sensitivity analysis and related comparisons.

Integrated multi-criteria group decision-making methods based on q-rung picture fuzzy sets for the identification of occupational hazards.

Practical group decision-making (DM) problems frequently involve challenging circumstances when attempting to assign appropriate values to the data because of the haziness and uncertainty of the surrounding circumstances. In order to address the ambiguity and imprecision that arise in DM issues, q-rung picture fuzzy sets (q-RPFSs) have a more broader structure. In this research, the criteria importance through intercriteria correlation (CRITIC) and the decision-making trial and evaluation laboratory (DEMATEL) techniques are separately integrated with the multi-attributive border approximation area comparison (MABAC) method. The MABAC method, which measures how far each alternative is from the border approximation area, is very stable and useful for resolving real-world problems. The CRITIC technique calculates the criteria weights by taking into account the relationships between attributes, and the DEMATEL methodology is recognized as the best method for determining how several criteria or factors interact with one another. As a result of these justifications, we made the decision to create the CRITIC-MABAC and DEMATEL-MABAC procedures for q-RPFSs. By using the suggested strategies, the primary goal of this article is to determine the occupational risk that has the greatest impact on the health of a hospital's medical staff. We begin by employing the CRITIC technique to determine the criteria weights. In addition, we calculate the weights of the criteria using the DEMATEL approach. The offered methodologies are investigated for their applicability to determine the most serious occupational hazard for hospital employees. We conducted a comparison with three earlier studies to verify the accuracy of the tactics that are offered.

Analysis of decision support system for determining industrial sub-district using DEMATEL-MABAC methods

This paper aims to create a decision support system (DSS) application for determining industrial locations in Serang Regency, with mathematical calculations using the DSS (Decision Support System) hybrid method namely Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Multi-Attributive Border Approximation Area Comparison (MABAC). The DEMATEL method is used to obtain the criteria weights of each criterion and the MABAC method is used to rank the determination the best industrial sub-districts. The data used are primary data, namely interviewing interviewees to calculate the weight of the criteria and secondary data, namely the official website data of Central Bureau of Statistics. Then, the process and results of the DEMATEL-MABAC calculation method are implemented with a python-based desktop application. The results of this method indicate that the location of Cikeusal District in Serang Regency is the right location to be used as an industrial location with the criteria and alternative function values ​​of 0.193.

A Systematic Literature Review of MABAC Method and Applications: An Outlook for Sustainability and Circularity

Multiple Criteria Decision-Making (MCDM) is one of the most reliable and applicable decision-making tools to address real-life complex and multi-dimensional problems in accordance with the concepts of sustainable development and circular economy. Although there have been several literature reviews on several MCDM methods, there is a research gap in conducting a literature review on the Multi-Attributive Border Approximation area Comparison (MABAC) as a useful technique to deal with intelligent decision-making systems. This study attempts to present a comprehensive literature review of 117 articles on recent developments and applications of MABAC. Future outlook is provided considering challenges and current trends.

Neutrosophic MABAC Method for Solutions of Ecotourism Centers (EC) in COVID-19

The Covid-19 epidemic has had devastating effects on the economy and generated many issues for enterprises worldwide. As a result, it is imperative that during periods of pandemic, options be made available to help impacted companies recover and enhance their operations. One industry that has encountered this issue and has had to overcome substantial obstacles is ecotourism centres. In the first part of this study, we offer several valuable and realistic action strategies for ecotourism centres. Tourism professionals, faculty members, executives, proprietors, and some staff from eco-tourism centres got together for brainstorming meetings to come up with implementation plans. The stated action plans are prioritised based on four factors. One MCDM approach, known as Multi-Attributive Border Approximation area Comparison (MABAC), uses distance and area-based computing algorithms to systematically represent a complicated choice. In this study, we suggest a bipolar neutrosophic MABAC that incorporates the three possible memberships truth, indeterminate, and false into a single set. Using a bipolar neutrosophic language scale, a panel of specialists was asked to rate the outcome values of requirements and options. The major output of the suggested approach is the distances of options from the Border Approximation Area of bipolar neutrosophic MABAC.

Extended MABAC method based on 2-tuple linguistic $ T $-spherical fuzzy sets and Heronian mean operators: An application to alternative fuel selection

<abstract><p>In recent years, fossil fuel resources have become increasingly rare and caused a variety of problems, with a global impact on economy, society and environment. To tackle this challenge, we must promote the development and diffusion of alternative fuel technologies. The use of cleaner fuels can reduce not only economic cost but also the emission of gaseous pollutants that deplete the ozone layer and accelerate global warming. To select an optimal alternative fuel, different fuzzy decision analysis methodologies can be utilized. In comparison to other extensions of fuzzy sets, the $ T $-spherical fuzzy set is an emerging tool to cope with uncertainty by quantifying acceptance, abstention and rejection jointly. It provides a general framework to unify various fuzzy models including fuzzy sets, picture fuzzy sets, spherical fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets and generalized orthopair fuzzy sets. Meanwhile, decision makers prefer to employ linguistic terms when expressing qualitative evaluation in real-life applications. In view of these facts, we develop an extended multi-attributive border approximation area comparison (MABAC) method for solving multiple attribute group decision-making problems in this study. Firstly, the combination of $ T $-spherical fuzzy sets with 2-tuple linguistic representation is presented, which provides a general framework for expressing and computing qualitative evaluation. Secondly, we put forward four kinds of 2-tuple linguistic $ T $-spherical fuzzy aggregation operators by considering the Heronian mean operator. We investigate some fundamental properties of the proposed 2-tuple linguistic $ T $-spherical fuzzy aggregation operators. Lastly, an extended MABAC method based on the 2-tuple linguistic $ T $-spherical fuzzy generalized weighted Heronian mean and the 2-tuple linguistic $ T $-spherical fuzzy weighted geometric Heronian mean operators is developed. For illustration, a case study on fuel technology selection with 2-tuple linguistic $ T $-spherical fuzzy information is also conducted. Moreover, we show the validity and feasibility of our approach by comparing it with several existing approaches.</p></abstract>

Decision Making Using the MABAC Method to Determine the Leading Small and Medium Industry Centers in Yogyakarta

Determining small-medium industries (SMIs) centers on producing SMIs capable of developing and excelling in Yogyakarta City. The determination of superior SMIs plays a crucial part in the development of new and creative industries. However, many unresolved SMIs decisions were made manually, thus making the long and ineffective process. Technology entry into various disciplines can make determining superior SMIs more efficient and systematic. To facilitate the determination of superior SMIs, it took advantage of the Decision Support System (DSS), where the author, when carrying out the analysis, applied the Multi-Attributive Border Approximation Area Comparison (MABAC) method for alternative rankings. This research resulted in the ranking of superior SMIs centers, namely alternatives (A6) ranked 1st, (A9) 2nd order, (A2) 3rd order, (A8) 4th order, (A10) 5th order, (A1) 6th order, (A3) 7th order, (A5) 8th order, (A4) 9th order, and (A7) 10th order. The MABAC method was successfully used in the decision-making of superior SMIs centers with a precision of 83.3% and an accuracy of 93.5%, calculated using a confusion matrix. The study’s results discovered that the MABAC approach was successfully used for decision-making for determining superior small and medium industry centers.

Implementasi Metode MABAC dalam Sistem Pendukung Keputusan Penentuan Lokasi Instalasi WI-FI Publik Oleh Dinas KominfoStan Kabupaten Deli Serdang

The need for public Wi-Fi installations is increasing with the aim of being able to meet the needs of the community in accessing the internet for free in public places. Thus, the Deli Serdang Regency Government through the Deli Serdang Regency KominfoStan Service installs a public Wi-Fi network with a limited budget every year. In determining the location of the public Wi-Fi installation, there are many public places, so that the Ministry of Communication and Information Technology is hesitant to determine the right location for the installation of public Wi-Fi. Decision Support System is applied in this study as a system for determining the location of public Wi-Fi installations. In determining the location of the right public Wi-Fi installation, it must meet criteria such as Distance, Accessibility, Economy, Crowd, and Facilities. Therefore, a Decision Support System (DSS) is needed in solving existing problems by applying the MABAC (Multi-Attributive Border Approximation area Comparison) method which can generate preference values from the first ranked alternative. So that the location for the installation of Public Wi-Fi is located on the A4 alternative, namely the Sultan Thaf Grand Mosque with a value of 0.480.