Induced 2-tuple linguistic generalized aggregation operators and their application in decision-making

Merigó, José M.; Gil‐Lafuente, Anna M.

doi:10.1016/j.ins.2013.02.039

Cited by 211 publications

(104 citation statements)

References 55 publications

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“…In recent studies, 2-tuple fuzzy linguistic representation model has been used in group MCDM problems successfully, e.g. material selection [12], product management [13] and computer network security systems evaluation [14]. In order to express individualized information fully for DMs, interval 2-tuple linguistic variable was defined by Lin et al [15] to better express decision information by relaxing constraint of choosing from a given linguistic term set.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS^*

Geng¹,

Gong²,

Chu³

2016

IJCIS

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Remanufacturing has been attracting attentions of global manufacturers as an important sustainable development strategy. Component oriented remanufacturing decision-making for complex product involving two phases is proposed in this paper. The first phase is to decide which components to be remanufactured using DEA. To overcome the drawback of traditional DEA without weight constraints, an augmented DEA is applied to evaluate the efficiencies of the pre-selected components considering manufacturing characteristic, comparative cost advantage and general returned status. The second phase is to select an appropriate remanufacturing concept for each efficient component. Interval 2-tuple linguistic model is used in obtaining and collecting experts' evaluations. Besides subjective experts' weights, the objective weights of them are considered in the group decision-making process, which are determined by the precision degree of information experts have given. TOPSIS integrated with interval 2-tuple fuzzy linguistic representation model is proposed to rank alternative remanufacturing concepts. A new distance measuring method between two interval 2-tuple vectors is given out considering both the subjective and objective criteria weights. The objective criterion weight is determined by the discrete degree of the performances of all alternatives on this criterion. A case study is carried out to demonstrate the effectiveness of the developed remanufacturing decision-making approach for complex product.

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Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS^*

Geng¹,

Gong²,

Chu³

2016

IJCIS

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“…Once the heterogeneous information is expressed in 2-tuple linguistic values in the BLTS, the 2-tuple linguistic computation model 23 can be carried out to compute linguistic results in S BLT S , using 2-tuple linguistic aggregation operators 30,31,40,42 .…”

Section: Transformation Of Fuzzy Sets Into 2-tuple Linguistic Valuesmentioning

confidence: 99%

Pure linguistic PROMETHEE I and II methods for heterogeneous MCGDM problems

Espinilla¹,

Halouani²,

Chabchoub³

2015

IJCIS

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The PROMETHEE methods basic principle is focused on a pairwise comparison of alternatives for each criterion, selecting a preference function type that often requires parameters in order to obtain a preference value. When a MCGDM problem is defined in an heterogeneous context, an adequate and common approach is to unify the involved information in linguistic values. However, for each criterion, there is a difficulty to select the specific preference function and define its parameters because they are expressed by crisp values in the unit interval, when the information involved in the problem has been unified into linguistic values. In this paper, a methodology for modeling linguistic preference functions in order to facilitate the selecting of each linguistic preference function type and the definition of its parameters is proposed, providing a more realistic definition of the criteria. Therefore, a generic linguistic preference function is proposed whose inputs and outputs are linguistic values. According to the generic linguistic preference function, six basic preference function types are extended for linguistic values. To do so, a linguistic difference function between linguistic values is defined, being its output, the input of the linguistic preference function. Furthermore, the proposed methodology is integrated in linguistic PROMETHEE I and II for heterogeneous MCGDM problems to obtain partial rankings and a full ranking of alternatives. So, the methodology provides pure linguistic PROMETHEE I and II that offer interpretability and understandability. Finally, the feasibility and applicability of pure linguistic PROMETHEE I and II are illustrated in a case study for the selection of a green supplier.

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“…E-mail address: peide.liu@gmail.com doi: 10.24200/sci.2017.4402 real numbers; however, it may be easy to do so by the linguistic terms. Up to now, the research on the linguistic MADM problems has led to many results [2][3][4][5][6][7]. Zadeh [8][9][10] rstly proposed the concept of the Linguistic Variable (LV).…”

Section: Introductionmentioning

confidence: 99%

“…Zhou and Chen [4] proposed some linguistic generalized power aggregation operators. Merig o and Gil-Lafuente [5] extended induced generalized OWA operator and the induced quasi-arithmetic Choquet integral operator to LVs.…”

Section: Introductionmentioning

confidence: 99%

2-Dimension Uncertain Linguistic Generalized Normalized Weighted Geometric Bonferroni Mean and Its Application in Multiple Attribute Decision Making

Лю

2017

Scientia Iranica

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KEYWORDS Aggregation operators;Multiple-attribute decision making; Bonferroni mean; 2-dimensional uncertain linguistic variables.Abstract. 2-Dimensional Uncertain Linguistic Variables (2DULVs) are powerful tools to express the fuzzy or uncertain information, and the weighted Bonferroni mean can not only take the attribute importance into account, but also capture the interrelationship between the attributes. However, the traditional Bonferroni mean can only deal with the crisp numbers. In this paper, Bonferroni mean was extended to process the 2DULVs. Firstly, we proposed the Normalized Weighted Geometric Bonferroni Mean (NWGBM) operator and the Generalized Normalized Weighted Geometric Bonferroni Mean (GNWGBM) operator, which had the characteristic of reducibility and considered the interrelationships between two attributes. Then, we introduced the computation rules, characteristics, the expected value, and comparison method of the 2DULVs. Further, we developed the 2-Dimensional Uncertain Linguistic Normalized Weighted Geometric Bonferroni Mean (2DULNWGBM) and the 2-Dimensional Uncertain Linguistic Generalized Normalized Weighted Geometric Bonferroni Mean (2DULGNWGBM), and explored some properties and discussed some special cases of them. Finally, we developed a new decision making method based on these operators. An example is given to compare the method with the existing methods.

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Induced 2-tuple linguistic generalized aggregation operators and their application in decision-making

Cited by 211 publications

References 55 publications

Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS^*

Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS^*

Pure linguistic PROMETHEE I and II methods for heterogeneous MCGDM problems

2-Dimension Uncertain Linguistic Generalized Normalized Weighted Geometric Bonferroni Mean and Its Application in Multiple Attribute Decision Making

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Induced 2-tuple linguistic generalized aggregation operators and their application in decision-making

Cited by 211 publications

References 55 publications

Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS*

Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS*

Pure linguistic PROMETHEE I and II methods for heterogeneous MCGDM problems

2-Dimension Uncertain Linguistic Generalized Normalized Weighted Geometric Bonferroni Mean and Its Application in Multiple Attribute Decision Making

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Product

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About

Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS^*

Component oriented remanufacturing decision-making for complex product using DEA and interval 2-tuple linguistic TOPSIS^*