A new mixed fuzzy-LP method for selecting the best supplier using fuzzy group decision making

Sepehriar, Abbas; Eslamipoor, Reza; Nobari, Arash

doi:10.1007/s00521-013-1458-z

Cited by 14 publications

(5 citation statements)

References 21 publications

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“…The linguistic variables and their corresponding grey numbers to evaluate alternatives are shown Table 4. [5,6] Good (G) [6,9] Very Good (VG) [9,10] Step 3: Normalizing the grey decision-making matrix (⊗̃). The normalized grey decision-making matrix is calculated by Eq.…”

Section: Copras -G Methodsmentioning

confidence: 99%

“…They are various supplier selection methods such as Data Envelopment analysis (DEA), Multi criteria decision making (MCDM) techniques, linear and goal programming, artificial neural network (ANN) and combined methods to use by researchers and practitioners [5]. Sepehriar et al proposed a linear mathematical modelling to weights of supplier selection criteria under fuzzy environment [6]. Fallahpour et al developed a hybrid model combined with AHP and multi expression programming (MEP) for supplier selection problem [7].…”

Section: Introductionmentioning

confidence: 99%

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An Integrated Interval type 2 fuzzy AHP and COPRAS-G methodologies for supplier selection in the era of Industry 4.0

Kaya

Ayçın

2021

Preprint

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Supply chain has a very extensive and dynamic structure that incorporates new business models, new customer expectations, market searches and technological developments. With the introduction of Industry 4.0 into supply chain, a rapid and intensive process of digitalization begin to transform every step of supply chain. Supply chain selection is one of the essential decisions in reducing the supply chain cost and improving overall quality of product and services. With the implication of digital technologies and Industry 4.0 on supply chain, the supplier selection process has been significantly changed during the recent years. Companies are willing to need new requirements for their own suppliers in accordance with Industry 4.0 implementations and technologies. This paper aims to identify key criteria to Industry 4.0 technologies and evaluate them to select the right suppliers selection in the era of Industry 4.0 Within the scope of this study attempts to develop an integrated Interval Type 2 Fuzzy AHP and GOPRAS-G methodology to select the appropriate supplier in the face of Industry 4.0 implementations. For this purpose, Interval Type 2 Fuzzy AHP was employed to weight the supplier evaluation criteria and then, Grey COPRAS method has been applied to prioritize suppliers. This paper is to provide practitioners and researchers with insight into how Industry 4.0 strategies influence on supplier selection.

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Section: Copras -G Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Integrated Interval type 2 fuzzy AHP and COPRAS-G methodologies for supplier selection in the era of Industry 4.0

Kaya

Ayçın

2021

Preprint

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“…Dursun and Karsak (2013) developed an integrated approach based on fuzzy QFD and the fuzzy weighted average (FWA) method for evaluation of suppliers. Sepehriar, Eslamipoor, and Nobari (2013) presented a hybrid approach for supplier selection and order allocation based on the fuzzy ELECTRE method and linear programming. Tseng and Chiu (2013) proposed a model for evaluating firms' green supply chain management based on the fuzzy set theory and grey relational analysis.…”

Section: Other Hybrid Approachesmentioning

confidence: 99%

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

Ghorabaee

Amiri

Zavadskas

et al. 2017

Economic Research-Ekonomska Istraživanja

122

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In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were:

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“…There are generally five schemes in handling the linguistic variable containing only one linguistic term: directly use linguistic labels [7,8], represent linguistic information using fuzzy membership functions [9][10][11][12], rely on the 2-tuple fuzzy linguistic representation model [13,14] and extended 2-tuple fuzzy linguistic models [15], employ the cloud model to depict the uncertainty of a qualitative concept [16,17], and utilize the linguistic scale functions to suit different semantic situations [18]. Meanwhile, uncertain linguistic variables [19] and their application in decision making are also carried out and can be found in many investigations [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

“…Formulae (9) and (12) are utilized in the whole illustration and a ¼ 1:4. Moreover, all criteria are of the maximizing type, and thus no normalization operations are required.…”

mentioning

confidence: 99%

Multi-criteria Group Decision-Making Approach Based on 2-Tuple Linguistic Aggregation Operators with Multi-hesitant Fuzzy Linguistic Information

Wang

Zhang

Chen

2015

Int. J. Fuzzy Syst.

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In practice, when the frequency of a linguistic term in evaluation information is greater than one, a consensus has been reached and this frequency is regarded to be one by default. However, in case that the frequencies of several elements in a dataset are not identical, their respective importance that was initially distinguishable will become indifferent in a routine processing, which may distort the original intention of decision-makers. As an extension of hesitant fuzzy linguistic term sets (HFLTSs) and hesitant fuzzy linguistic sets (HFLSs), multi-hesitant fuzzy linguistic term sets (MHFLTSs) are thus proposed on the basis of multi-hesitant fuzzy sets (MHFSs) in this paper, and each multi-hesitant fuzzy linguistic term element (MHFLTE) can contain inconsecutive and repeatable linguistic terms. Besides, inspired by the 2-tuple linguistic model and linguistic scale functions, the transformation functions among linguistic terms, 2-tuples, and numerical data are constructed in a generalized form to cope with different semantics. According to practical conditions, decision-makers' preferences, or experts' suggestions, various functions can be chosen after some necessary adjustments. In this way, the original essence of vague evaluations can be retained properly and the accuracy and reliability of final results could be further improved. Furthermore, the basic operations and comparison method of MHFLTEs are given on the basis of the transformation functions, and some 2-tuple linguistic aggregation operators of MHFLTEs are also provided to deal with problems where the criteria weights are known or unknown. Based on these prerequisites, a multi-criteria group decision-making approach is established to process multi-hesitant fuzzy linguistic information. The validity and effectiveness of the proposed approach are finally demonstrated through illustration and comparison analysis.Keywords Multi-hesitant fuzzy linguistic term sets (MHFLTSs) Á 2-Tuple linguistic model Á Multi-criteria group decision making (MCGDM) Á Aggregation operator

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A new mixed fuzzy-LP method for selecting the best supplier using fuzzy group decision making

Cited by 14 publications

References 21 publications

An Integrated Interval type 2 fuzzy AHP and COPRAS-G methodologies for supplier selection in the era of Industry 4.0

An Integrated Interval type 2 fuzzy AHP and COPRAS-G methodologies for supplier selection in the era of Industry 4.0

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

Multi-criteria Group Decision-Making Approach Based on 2-Tuple Linguistic Aggregation Operators with Multi-hesitant Fuzzy Linguistic Information

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