Multi-attributive Border Approximation Area Comparison Research Articles

Blending Uncertainty Theory Innovative into Decision Support Framework for Selecting Agricultural Machinery Suppliers

The rivalry among suppliers and stakeholders created pressure, making the selection of the best provider a crucial subject based on a set of criteria for the responsiveness of clients. Consequently, several criteria need to be considered to select the most suitable supplier. As a result, certain criteria may overlap and contradict one another. Multi-criteria decision-making (MCDM) techniques are widely used in many fields to address selection problems when there are numerous competing criteria and multiple alternatives. Hence, we are leveraging MCDM techniques in constructing a decision support framework (DSF) as MEthod based on the Removal Effects of Criteria (MEREC) and Multi-Attributive Border Approximation Area Comparison (MABAC). In our DSF, we harnessed the uncertainty theory of triangular neutrosophic sets (TrNSs) which is considered one of the advantages that DSF provides.TrNSs support experts in their judgments when facing problems such as imprecise judgments and insufficient data. As well, we applied the constructed DSF in a real case study for five suppliers for machinery agriculture and evaluated the suppliers based on ten criteria. The DSF’s findings indicated that supplier 5 is the optimal one for machinery agriculture otherwise supplier 2 is the worst one. Also, we applied another ranker technique of MCDM technique entailed in the weighted sum model (WSM) and compared WSM results with MABAC under the authority of TrNSs.

Multi-objective capacity configuration optimization of the combined wind - Storage system considering ELCC and LCOE

The optimal capacity configuration of combined wind-storage systems (CWSSs) serves as a foundation and premise for building new electricity system. This paper proposes a novel capacity configuration model of CWSS. The model simultaneously considers economy, stability and low carbon by respectively minimizing Levelized cost of electricity (LCOE) and maximizing effective load carrying capacity (ELCC). The multi-objective optimization model is solved by Non-dominated Sorting Genetic Algorithm II (NSGA-II). And Multi-Attributive Border Approximation Area Comparison (MABAC) method is used to score the alternative solutions on the Pareto front and make decisions under different scenarios. The results of the case study show that: (1) The evaluation of the ELCC for CWSS can quantify its ability to replace the installed capacity of thermal power, thus greatly reducing the uncertainty of wind power output. (2) Under low-carbon scenario, economic scenario and standard scenario, the results of optimal capacity configuration for the CWSS show that LCOE and ELCC are negatively correlated. When the weights of ELCC and LCOE are equal, the three goals of economy, low carbon and safety and stability are achieved. (3) The results of a single sensitivity analysis on LCOE show that the sensitivity coefficient of electricity generation is the highest, exerting the greatest impact on the capacity configuration decision of the CWSS. A 20 % increase in power generation can reduce LCOE by 0.1203RMB/kWh. This paper provides energy planning recommendations for decision-makers in CWSSs, contributing to the development of a reliable new electricity system.

Beyond throughput: Evaluating maritime port competitiveness using MABAC and Bayesian methods

The performance ranking framework of maritime ports conducted by the World Shipping Council relies solely on a singular criterion, such as container throughput. This ranking method lacks a comprehensive assessment of port competitiveness and may have biases. Therefore, this work proposes a new approach to measure the competitiveness of maritime ports by considering multiple performance criteria, such as port processing time, bunker fuel quality, bunker fuel suppliers, geographical advantages, and port security. To ensure fairness in weight estimation, both objective method (using the Entropy method) and subjective method (using the Best Worst method) are employed and integrated using Bayes’ theorem. Furthermore, the Multi-Attributive Border Approximation Area Comparison (MABAC) method is utilized to evaluate the ranking of ports based on the combined effect of these criteria, referred to as the Port Competitiveness Index (PCI). To test the effectiveness of the proposed methodology, the top 20 major maritime ports on the Asia-Europe service route are determined. This finding highlights the practical insights gained from the study, which can be applied to improve the performance of ports across different service routes worldwide.

Evaluation of agile attributes for low-cost carriers to achieve sustainable development using an integrated MCDM approach

PurposeSince conducting agile strategies provides sustainable passenger satisfaction and revenue by replacing applied policies with more profitable ones rapidly, the focus of this study is to evaluate agile attributes for managing low-cost carriers (LCCs) operations by means of resources and competences based on dynamic capabilities built on resource-based view (RBV) theory and to achieve sustainable competitive advantage in a volatile and dynamic air transport environment. LCCs in Turkey are also evaluated in this study since the competition among LCCs is high to gain market share and they can adapt quickly to all kinds of circumstances.Design/methodology/approachTwo well-known Multi-Criteria Decision-Making Methods (MCDM) named as the Stepwise Weight Assessment Ratio Analysis (SWARA) and multi-attributive border approximation area comparison (MABAC) methods by employing Picture fuzzy sets (PiFS) are employed to determine weight of agile attributes and superiority of LCCs based on agile attributes in the market, respectively. To check the consistency and robustness of the results for the proposed approach, comparative and sensitivity analysis are performed at the end of the study.FindingsWhile the ranking orders of agile attributes are Strategic Responsiveness (AG1), Financial Management (AG4), Quality (AG2), Digital integration (AG3) and Reliability (AG5), respectively, LCC2 is selected as the best agile airline company in Turkey with respect to agile attributes. SWARA and MABAC method based on PiFS is appropriate and effective method to evaluate agile attributes that has important reference value for the airline companies in aviation industry.Practical implicationsThe findings of this study will support managers in the airline industry to conduct airline operations more flexibly and effectively to take sustainable competitive advantage in unexpected and dynamic environment.Originality/valueTo the author' best knowledge, this study is the first developed to identify the attributes necessary to increase agility in LCCs. Thus, as a systematic tool, a framework is developed for the implementation of agile attributes to achieve sustainable competitive advantage in the airline industry and presented a roadmap for airline managers to deal with crises and challenging situations by satisfying customer and increasing competitiveness.

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.

A Parameter Reduction-Based Decision-Making Method with Interval-Valued Neutrosophic Soft Sets for the Selection of Bionic Thin-Wall Structures.

Bio-inspired thin-wall structures with excellent mechanical properties, high-energy absorption capabilities, and a desirable lightweight level have been extensively applied to the passive safety protection of transportation and aerospace. Collaboration matching and the selection of optional structures with different bionic principles considering the multiple attribute evaluation index and engineering preference information have become an urgent problem. This paper proposes a parameter reduction-based indifference threshold-based attribute ratio analysis method under an interval-valued neutrosophic soft set (IVNS-SOFT) to obtain the weight vector of an evaluation indicator system for the selection of bionic thin-wall structures, which can avoid the problem of an inadequate subjective evaluation and reduce redundant parameters. An IVNS-SOFT-based multi-attributive border approximation area comparison (MABAC) method is proposed to obtain an optimal alternative, which can quantify uncertainty explicitly and handle the uncertain and inconsistent information prevalent in the expert system. Subsequently, an application of five bio-inspired thin-wall structures is applied to demonstrate that this proposed method is valid and practical. Comparative analysis, sensitivity analysis, and discussion are conducted in this research. The results show that this study provides an effective tool for the selection of bionic thin-wall structures.

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.

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