Fuzzy group decision-making for multi-format and multi-granularity linguistic judgments in quality function deployment

Zhang, Zaifang; Chu, Xuening

doi:10.1016/j.eswa.2008.12.027

Cited by 104 publications

(63 citation statements)

References 38 publications

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“…There are many multi-objective decision-making methods using scaling, and the characteristics of a rule could give an appropriate tips of scale. In this paper, the scale is based on the utility function similar to the function of Promethee [2]. We maybe use other scale, and use the scale only to simple the problem.…”

Section: Multi-objective Decision-making Problemmentioning

confidence: 99%

A New Stability Analysis Approach of Multi-objective Decision Functions Based on GP Algorithm Theory

Wang¹,

Xia²

2017

dtssehs

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Abstract. In multi-objective decision proplems many values must be assigned, such as the importance of the different objective and the values of the alternatives with respect to subjective objective.In this paper we propose a new construct method of multi-objective decision functions based on genetic programming algorithm, which produces more stable decision functions than the AHP arithmetic mean used ones. The theoretical expectations are validated by case studies.

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Section: Multi-objective Decision-making Problemmentioning

confidence: 99%

A New Stability Analysis Approach of Multi-objective Decision Functions Based on GP Algorithm Theory

Wang¹,

Xia²

2017

dtssehs

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“…Chan and Wu [8] suggested a systematic approach to QFD on the basis of symmetrical triangular fuzzy numbers (STFNs) to capture the vagueness in linguistic assessments from both customers and technicians. Zhang and Chu [10] proposed a fuzzy group decision-making approach incorporating with two optimization models (i.e., logarithmic least squares model and weighted least squares model) to aggregate the multi-format and multi-granularity linguistic judgments of decision makers for constructing the HoQ. Yan and Ma [33] proposed a two-stage group decision-making approach to tackle with human subjective perception and customer heterogeneity underlying QFD, in which the order-based semantics of linguistic information is used to derive the fuzzy preference relations of different DRs with respect to each customer and the fuzzy majority is used to synthesize all customers' individual fuzzy preference relations to determine the prioritization of DRs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It is common for QFD team members to use linguistic terms to express their judgments [4,10]. Moreover, because of uncertainty and incompleteness in the early stage of new product development, a single linguistic term may not suitable or adequate for QFD team members to give their assessments in constructing the HoQ.…”

Section: Introductionmentioning

confidence: 99%

Uncertain Quality Function Deployment Using a Hybrid Group Decision Making Model

2016

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Quality function deployment (QFD) is a widely used quality system tool for translating customer requirements (CRs) into the engineering design requirements (DRs) of products or services. The conventional QFD analysis, however, has been criticized as having some limitations such as in the assessment of relationships between CRs and DRs, the determination of CR weights and the prioritization of DRs. This paper aims to develop a new hybrid group decision-making model based on hesitant 2-tuple linguistic term sets and an extended QUALIFLEX (qualitative flexible multiple criteria method) approach for handling QFD problems with incomplete weight information. First, hesitant linguistic term sets are combined with interval 2-tuple linguistic variables to express various uncertainties in the assessment information of QFD team members. Borrowing the idea of grey relational analysis (GRA), a multiple objective optimization model is constructed to determine the relative weights of CRs. Then, an extended QUALIFLEX approach with an inclusion comparison method is suggested to determine the ranking of the DRs identified in QFD. Finally, an analysis of a market segment selection problem is conducted to demonstrate and validate the proposed QFD approach.

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“…Therefore, data collected from decision makers on the importance of requirements are usually subjective and uncertain. To reduce the bias and partiality that can faced during the decision process, QFD widely utilizes group decision making (GDM) [11][12][13][14] and fuzzy set theory [15][16][17][18][19] . In a GDM process, different alternatives are assessed by a predefined group of decision makers (DMs) who without doubt differ in their education, background, competence, experience, and character.…”

Section: Introductionmentioning

confidence: 99%

An Extended Quality Function Deployment Incorporating Fuzzy Logic and GDM Under Different Preference Structures

Büyüközkan¹,

Çifçi²

2015

IJCIS

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The paper proposes a fuzzy logic-based group decision making (GDM) approach, which can be used for quality function deployment (QFD) in the development of product improvement strategies. Decision makers can state their preferences in various ways, including incomplete preferences which are difficult to evaluate in a coherent way. We extend the QFD methodology by using a GDM approach which considers multiple preference formats and incomplete information. Finally, a numerical analysis for "Portable Entertainment and Game Systems" design is given to verify the feasibility of the model.

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Fuzzy group decision-making for multi-format and multi-granularity linguistic judgments in quality function deployment

Cited by 104 publications

References 38 publications

A New Stability Analysis Approach of Multi-objective Decision Functions Based on GP Algorithm Theory

A New Stability Analysis Approach of Multi-objective Decision Functions Based on GP Algorithm Theory

Uncertain Quality Function Deployment Using a Hybrid Group Decision Making Model

An Extended Quality Function Deployment Incorporating Fuzzy Logic and GDM Under Different Preference Structures

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