An Extended Copras Model for Multiple Attribute Group Decision Making Based on Single-Valued Neutrosophic 2-Tuple Linguistic Environment

Wei, Guiwu; Wu, Jihuai; Guo, Yanfeng; Wang, Jie; Wei, Cun

doi:10.3846/tede.2021.14057

Cited by 51 publications

(30 citation statements)

References 33 publications

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“…Green supplier selection, computer aided evaluation, and artificial intelligence simulation decision are the future research direction [41][42][43]. rough comparative analysis and sensitivity analysis, some revelations are obtained:…”

Section: Discussionmentioning

confidence: 99%

Rational Supplier Selection Based on Two-Phase Deep Analysis considering Fuzzy QFD and Game Theory

Feng

Luo

Wang

et al. 2021

Mobile Information Systems

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Viewing from the perspective of a traditional manufacturing enterprise, the paper proposes a fuzzy comprehensive evaluation system model, which selects the most suitable supplier or suppliers to undertake the supply tasks and to achieve the purposes of reducing procurement costs and improving the supply quality and reliability, so as to fully meet customer demands. Based on decision-makers’ preferences and suppliers’ supply capabilities, subjective and objective weight of criteria are both developed for supplier selection with the corresponding weighting method, namely, quality function deployment (QFD) and entropy weight. Specially, the two-phase fuzzy QFD method combined with the trapezoidal fuzzy number (TFN) is creatively applied to realize the complicated conversion process. Furthermore, the game theory is employed to combine the advantages of the subjective and objective weighting method, by which the comprehensive weight can be determined. A numerical example is given to demonstrate the proposed modeling process. Through programming drawing images for comparative analysis and sensitivity analysis, study image trends, and draw conclusions, the proposed model effectively alleviates the weight deviation and has higher rationality and extensibility in supplier selection.

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Section: Discussionmentioning

confidence: 99%

Rational Supplier Selection Based on Two-Phase Deep Analysis considering Fuzzy QFD and Game Theory

Feng

Luo

Wang

et al. 2021

Mobile Information Systems

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“…Another area for future research could be to apply the proposed method to real-world problems, such as designing geographic information systems, economic indicators assessment, evaluations in tourism management, and pollution management [2,[73][74][75]. Future research can be enriched by the proposed method in a vaguely determined environment, e.g., fuzzy and neutrosophic environments [3,76,77].…”

Section: Discussionmentioning

confidence: 99%

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

et al. 2021

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The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, called MEREC (MEthod based on the Removal Effects of Criteria), to determine criteria’ objective weights. This method uses a novel idea for weighting criteria. After systematically introducing the method, we present some computational analyses to confirm the efficiency of the MEREC. Firstly, an illustrative example demonstrates the procedure of the MEREC for calculation of the weights of criteria. Secondly, a comparative analysis is presented through an example for validation of the introduced method’s results. Additionally, we perform a simulation-based analysis to verify the reliability of MEREC and the stability of its results. The data of the MCDM problems generated for making this analysis follow a prevalent symmetric distribution (normal distribution). We compare the results of the MEREC with some other objective weighting methods in this analysis, and the analysis of means (ANOM) for variances shows the stability of its results. The conducted analyses demonstrate that the MEREC is efficient to determine objective weights of criteria.

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“…MCDM models are applied to identify and select the best possible solution from a set of alternatives based on different decision criteria. For example, prior research has used COPRAS to plan water transfer between basins (Roozbahani et al 2020), rank hybrid wind farms (Dhiman and Deb 2020), select green suppliers (Kumari and Mishra 2020), evaluate the performance of contractors (Jasim 2021), assess construction project safety (Wei et al 2021), rank effective risks in natural gas supply projects (Balali et al 2021), and evaluate COVID-19 regional safety (Hezer et al 2021). In addition, previous studies have used MULTIMOORA for selecting suppliers (Tavana et al 2020a, b) and logistic service providers (Sarabi and Darestani 2021), examining the barriers to the adoption of renewable energy (Asante et al 2020), selecting car subscription station sites (Lin et al 2020a, b), choosing stable battery suppliers (Wang et al 2021a, b), and evaluating technology project review experts (Wang et al 2021c, d).…”

Section: Copras Multimoora and Topsismentioning

confidence: 99%

An integrated fuzzy sustainable supplier evaluation and selection framework for green supply chains in reverse logistics

Tavana

Shaabani

Santos‐Arteaga

et al. 2021

Environ Sci Pollut Res

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Green supply chain management considers the environmental effects of all activities related to the supply chain, from obtaining raw materials to the final delivery of finished goods. Selecting the right supplier is a critical decision in green supply chain management. We propose a fuzzy green supplier selection model for sustainable supply chains in reverse logistics. We define a novel hierarchical fuzzy best-worst method (HFBWM) to determine the importance weights of the green criteria and sub-criteria selected. The fuzzy extension of Shannon's entropy, a more complex evaluation method, is also used to determine the criteria weights, providing a reference comparison benchmark. Several hybrid models integrating both weighting techniques with fuzzy versions of complex proportional assessment (COPRAS), multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA), and the technique for order of preference by similarity to ideal solution (TOPSIS) are designed to rank the suppliers based on their ability to recycle in reverse logistics. We aggregate these methods' ranking results through a consensus ranking model and illustrate the capacity of relatively simple methods such as fuzzy COPRAS and fuzzy MOORA to provide robust rankings highly correlated with those delivered by more complex techniques such as fuzzy MULTIMOORA. We also find that the ranking results obtained by these hybrid models are more consistent when HFBWM determines the weights. A case study in the asphalt manufacturing industry is presented to demonstrate the proposed methods' applicability and efficacy.

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An Extended Copras Model for Multiple Attribute Group Decision Making Based on Single-Valued Neutrosophic 2-Tuple Linguistic Environment

Cited by 51 publications

References 33 publications

Rational Supplier Selection Based on Two-Phase Deep Analysis considering Fuzzy QFD and Game Theory

Rational Supplier Selection Based on Two-Phase Deep Analysis considering Fuzzy QFD and Game Theory

Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC)

An integrated fuzzy sustainable supplier evaluation and selection framework for green supply chains in reverse logistics

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