Intuitionistic Fuzzy MOORA for Supplier Selection

Pérez-Domínguez, Luis; Alvarado‐Iniesta, Alejandro; Rodríguez-Borbon, Iván; Villegas, Osslan Osiris Vergara

doi:10.15446/dyna.v82n191.51143

Cited by 39 publications

(15 citation statements)

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“…Govindan et al (2015) used the decision-making trial and evaluation laboratory (DEMATEL) method with intuitionistic fuzzy sets to handle the important and causal relationships between green supply chain management (GSCM) practices and performances. Pérez-Domínguez et al (2015) developed a hybrid method between MOORA and intuitionistic fuzzy sets for the selection of suppliers with a focus on multi-criteria and multi-group environment. Shahryari Nia et al (2016) used a modified Delphi method to determine supplier selection criteria.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling supplier selection in the era of Industry 4.0

Sachdeva¹,

Shrivastava

Chauhan

2019

BIJ

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Purpose The problem of evaluating potential suppliers has always been based on finding an optimal tradeoff between supplier’s performance consistently meeting firms’ needs and acceptable cost. The purpose of this paper is to propose a hybrid multi-criteria decision framework to quantify this qualitative judgment and reduce ambiguity in selection of suppliers in the era of Industry 4.0. Design/methodology/approach A hybrid intuitionistic fuzzy entropy weight-based multi-criteria decision model with TOPSIS is proposed. The authors make use of the intuitionistic fuzzy weighted approach operator for aggregating individual decision maker’s opinions regarding each alternative over every criterion. Additionally, the authors employ the concept of Shannon’s entropy to calculate the criteria weights. Findings Results obtained on the basis of the proposed hybrid methodology are analyzed against two more cases wherein the authors try to showcase the relevance of using IFS and entropy-based decision framework and find out the uniqueness of the proposed framework in supplier selection process. Practical implications The proposed model is apposite to solve management problem of supplier selection in two ways: aggregating individual decision maker’s opinion for each of the predefined criteria along with individual decision maker’s importance and ranking the suppliers based on both positive and negative ideal solutions using TOPSIS. Originality/value A robust framework incorporates not only suppliers’ performance but also provides weightage to key decision makers. Especially in the context of MCDMs wherein both qualitative and quantitative data is evaluated simultaneously, the proposed framework is unique in its practical implementation of reducing ambiguity in the supplier selection process.

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Section: Literature Reviewmentioning

confidence: 99%

Modeling supplier selection in the era of Industry 4.0

Sachdeva¹,

Shrivastava

Chauhan

2019

BIJ

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“…The MOORA method is the method introduced by Braurers and Zavadkas [14]. This relatively new method is used by Braurers in a multi-criteria decision making.…”

Section: Multi-objective Optimization On the Basis Of Ratio Analysismentioning

confidence: 99%

Multi-Objective Optimization Method by Ratio Analysis in Determining Results in Decision Support Systems

Siahaan¹

2018

Preprint

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Decision support system in selecting a product aims to improve the company's performance in the selection of certain products. This system is excellent to apply to companies, especially in companies that produce goods. It is so that consumers will not experience disappointment in the selection of these items. Every company needs a decision support system that can help choose the best product results accurately based on predetermined criteria. It is to avoid fatal errors. Therefore a company is beneficial and makes decision making more comfortable, in the selection of goods. The method used in this study is Multi-Objective Optimization on the Base of Ratio Analysis (MOORA). Selection of product results will be more structured and achieved using the MOORA method. Companies in the selection of goods will be under the desired target and can also minimize errors.

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“…(2) Research on the decision making methods, mainly include: extensions of the traditional decision making methods to intuitionistic fuzzy sets, such as TOPSIS (Wang et al 2015), VIKOR (Peng et al 2015), ELECTRE (Liu, Zhang 2011;Ebrahimnejad et al 2015;Hashemi et al 2016), TODIM (Li et al 2015), DEMATEL (Govindan et al 2015), MOORA (Pérez-Domínguez et al 2015), MULTIMOORA , COPRAS (Hajiagha et al 2013a), DEA (Hajiagha et al 2013b; and so on are extended to intuitionistic fuzzy information, we can call these extensions the extended decision making methods; another decision making methods are based on the aggregation operators, and can provide the comprehensive values by aggregating the criteria information. (3) Research on intuitionistic fuzzy group decision-making, mainly include: the construction of aggregation rules for intuitionistic fuzzy information, the optimization modeling construct, conflict measure models of group members, group consistency analysis models and the optimal selection of the project etc.…”

Section: The Research Progress Of Intuitionistic Fuzzy Sets In Econommentioning

confidence: 99%