Multi-attributive Border Approximation Area Research Articles

Evaluation and prioritization of barriers to the implementation of the eco-regenerative supply chains using fuzzy ZE-numbers framework in group decision-making

<p>In today's supply chain management, there is a growing emphasis on transitioning to environmentally sustainable practices. This paper aimed to identify and rank the barriers to the implementation of eco-regenerative supply chains. A novel integrated approach was proposed based on stepwise weighted assessment ratio analysis (SWARA) and the multi-attributive border approximation area (MABAC) method using ZE-fuzzy numbers. This approach aimed to address some of the limitations of the failure mode and effects analysis (FMEA) method, including lack of thorough prioritization and inability to make decisions about the importance of various failure factors in an uncertain environment. By combining fuzzy sets and considering the reliability levels of two distinct groups of decision-makers and experts, this proposed method offers a comprehensive evaluation framework. Following the determination of the risk priority number (RPN) by the FMEA method, risk factors were evaluated using ZE-SWARA, and barriers were ranked using the ZE-MABAC method to identify critical barriers and propose corrective actions. Furthermore, sensitivity analysis was conducted in this study to demonstrate the viability of the proposed method. This research contributes to the advancement of eco-regenerative supply chain management practices by offering a systematic and innovative approach to addressing environmental concerns and improving decision-making processes in uncertain environments.</p>

Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry.

The assessment of sustainable supplier is very significant for supply chain management (SCM). The procedure of sustainable supplier selection (SSS) is a complex process for decision experts (DEs) due to the association of diverse qualitative and quantitative attributes. As the uncertainty is usually ensued in the SSS and hesitant fuzzy set (HFS), an extension of fuzzy set (FS) has been demonstrated as one of the effective ways to treat the uncertain information in realistic problems. The objective of this paper is to propose an integrated hesitant fuzzy–data envelopment analysis (DEA)–full consistency method (FOCUM)–multi attribute border approximation area comparison (MABAC) method called HF-DEA-FUCOM-MABAC framework to assess the multi-attribute decision-making (MADM) problems on HFSs settings. In this line, first, the efficient alternatives are chosen using the DEA method. Second, The FUCOM is used to compute the subjective weight of attributes. Third, The HF-MABAC method is presented to prioritize the alternatives in an MADM problem. In the following, a case study of SSS problem for an Auto-making company is taken to show the practicality and utility of the presented approach. Next, we present a sensitivity investigation with different attribute weights set to observe the steadiness of the presented approach. Finally, we draw attention toward a comparison between presented approach with the extant HF-FOCUM-TOPSIS model to show its advantage and potency as well.

A FMEA based novel intuitionistic fuzzy approach proposal: Intuitionistic fuzzy advance MCDM and mathematical modeling integration

This study proposes a novel three-stage intuitionistic fuzzy risk assessment (RA) approach based on Failure Modes and Effects Analysis (FMEA). In this study, it was paid attention for considering real constraints of firms such as capital, time etc. to prevent nan-fatal failure modes (FMs), interactions between FMs and risk level similarities created by risk factors (RFs). At the first stage of the proposed approach, RFs’ weights are computed by a new intuitionistic fuzzy weighting method considering similarities between RFs for risk levels that they can create. At the second stage, Modified Intuitionistic Fuzzy Multi Attribute Border Approximation Area (MIF-MABAC) including interactions between FMs is used to determine the rankings of FMs by using Extended Haussdorff distance function. At the third stage, two intuitionistic fuzzy mathematical models are established to show the effect of the real constraints of the firm to identify the risk types (RTs) that must be avoided primarily. It was seen that the first model gives the same ranking results with the MIF-MABAC. Additionally, when including the real constraints, the first model can give the more suitable results than the second model. The results obtained from the first model show that experts’ assessments and mathematical modeling identify the same FMs for preventing primarily. This study is the first one to suggest a new RA approach that reflects the real constraints of the firms to RA. Additionally, this is the first study that models’ interactions between FMs and risk level similarities created by RFs.

Application of a D Number based LBWA Model and an Interval MABAC Model in Selection of an Automatic Cannon for Integration into Combat Vehicles

A decision making procedure for selection of a weapon system involves different, often contradictory criteriaand reaching decisions under conditions of uncertainty. This paper proposes a novel multi-criteria methodology based on D numbers which enables efficient analysis of the information used for decision making. The proposed methodology has been developed in order to enable selection of an efficient weapon system under conditions when a large number of hierarchically structured evaluation criteria has to be processed. A novel D number based Level Based Weight Assessment – Multi Attributive Border Approximation area Comparison (D LBWA-MABAC) model is used for selection of an automatic cannon for integration into combat vehicles. Criteria weights are determined based on the improved LBWA-D model. The traditional MABAC method has been further developed by integration of interval numbers. A hybrid D LBWA-MABAC framework is used for evaluation of an automatic cannon for integration into combat vehicles. Nine weapon systems used worldwide have been ranked in this paper. This multicriteria approach allows decision makers to assess options objectively and reach a rational decision regarding the selection of an optimal weapon system. Validation of the proposed methodology is performed through sensitivity analysis which studies how changes in the weights of the best criterion and the elasticity coefficient affect the ranking results.

Izbor protivoklopnih vođenih raketa modelom višekriterijumskog odlučivanja

Introduction: Anti Tank Ground Missiles (ATGMs) are one of the most efficient weapon systems to counter armored and mechanized units. Procurement of these weapons is imperative for armed forces of any country. Adequate evaluation and choice of an efficient ATGM system is a very important factor which affects operational capabilities of armed forces. The purpose of this paper is to present that multi criteria methods can be a useful tool for optimal procurement of ATGMs for armed forces. Methods: The implementation of the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and the MABAC (Multi Attributive Border Approximation Area Comparison) multi criteria methods will be proposed for decision makers to solve the problem of ATGM procurement. In this paper, four models of ATGMs will be proposed as possible solutions. These ATGMs will be presented as alternatives A1, A2, A3 and A4. Results: The implementation of the methods in this paper has led to the conclusion that the alternative A2 has the highest value and therefore the best course of action for decision makers is to chose procurement of this model of ATGMs. Conclusion: The conclusion is that the mathematical models of multi-criteria decision making presented in this paper unequivocally point to the alternative with the best characteristics, thus presenting extremely useful tools for decision makers.

Penerapan Metode MABAC Untuk Mendukung Pengambilan Keputusan Pemilihan Kepala Cabang Pada PT. Cefa Indonesia Sejahtera Lestari

The election of the branch head is prioritized to support the performance process and the continuous control process so in the election must have criteria that are able to give the right decision the criteria in question are education, experience, absenteeism and responsibility. Election of branch heads at PT. Cefa Indonesia Prosperous Lestari is carried out by receiving files from the company secretary's report, then an assessment is made based on predetermined criteria. The author chose the MABAC method (MULTI ATTRIBUTIVE BORDER APPROXIMATION AREA COMPARISON). used to analyze different alternatives and estimate alternatives according to their level of ultility where the values of the attributes are expressed in intervals to increase efficiency and improve accuracy in the decision making process.

MULTI-CRITERIA MODEL BASED ON LINGUISTIC NEUTROSOPHIC NUMBERS: THE SELECTION OF UNMANNED AIRCRAFT

<jats:p>The paper presents a new approach in treating uncertainty and subjectivity in the decision making process based on the modification of Multi Attributive Border Approximation area Comparison (MABAC) and an Objective-Subjective (OS) model by applying linguistic neutrosophic numbers (LNN) instead of traditional numerical values. By integrating these models with linguistic neutrosophic numbers it was shown that it is possible to a significant extent to eliminate subjective qualitative assessments and assumptions by decision makers in complex decision-making conditions. On this basis, a new hybrid LNN OS-MABAC model was formed. This model was tested and validated on a case-study of the selection of optimal unmanned aircraft intended to combat forest fires.</jats:p>