• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.75-84
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• 1994

The uncertainty in the relative weights of a pairwise comparison matrix n Multi-attribute Decision Making (MADM) is caused by imprecise preference information of decision maker. In this paper, it is shown how weight of attributes can be derived from the pairwise comparison matrix with interval pairwise comparison. The preference information of each pair of attributes with a point pairwise comparison is combined with an interval pairwise comparison in order to estimate a point pairwise comparison for a pair of attributes with the imprecise preference information. A numerical example shows the suggested procedure for deriving weights of attributes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.186-193
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• 1996

This paper presents a fuzzy structural modeling using the concept of Saaty's pairwise comparison matrix. The merit of this approach can be reduced the number of pairwise comparison.

• Structural Engineering and Mechanics
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• v.6 no.1
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• pp.17-30
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• 1998

The method of pairwise comparison inherently contains information of ambiguity, fuzziness and conflict in design goals for a multiobjective structural design. This paper applies the principle of paired comparison so that the vaguely formulated problem can be modified and a set of numerically acceptable weight would reflect the relatively important degree of multiple objectives. This paper also presents a fuzzy global criterion method ($FGCM_{\lambda}$) included fuzzy constraints that coupled with the objective weighting rank obtained from the modified pairwise comparisons for fuzzy multiobjective optimization problems. Descriptions in sequence of this combined method and problem solving experiences are given in the current article. Multiobjective design examples of truss and mechanical spring structures illustrate this optimization process containing the revising judgement techniques.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.119-134
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• 2004

Generally to estimate the priority vector in AHP, an eigen-vector method or a log-arithmic least square method is applied to pairwise comparison matrix itself. In this paper an estimating method is suggested, which is applied to pairwise comparison matrix adjusted by using the eigen-decomposition of skew-symmetric matrix. We also show theoretical background, meanings, and several advantages of this method by example. This method may be useful in case that pairwise comparison matrix is quite inconsistent.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.531-541
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• 2012

In this study, we consider various methods to estimate the weights of a pairwise comparison matrix in the Analytic Hierarchy Process widely applied in various decision-making fields. This paper uses a data dependent simulation to evaluate the statistical accuracy, minimum violation and minimum norm of the obtaining weight methods from a reciprocal symmetric matrix. No method dominates others in all criteria. Least squares methods perform best in point of mean squared errors; however, the eigenvectors method has an advantage in the minimum norm.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.1
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• pp.1-6
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• 2010

The Analytic Hierarchy Process (AHP) has been applied widely in various decision making fields. One of advantages of the AHP is the consistency test. However, it has several problems such as the limit of its concept, the limit of 9 scales and stern criteria, contradictory pairwise comparison. In this paper, we propose new criteria for the consistency with more realistic and ideal conditions. To derive the criteria, we conduct the simulation and use the bootstrap method, which is one of resampling techniques in the simulation area.

• Transactions of Materials Processing
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• v.12 no.5
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• pp.465-472
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• 2003

Engineering design can be viewed as a decision making process, which involves the nonlinear tradeoffs task among the multiple conflicting attributes and considers the robustness of design. In order to obtain best engineering design, methodology for accurate assessment of his/her preference about the multiple attributes is required. Conventionally, intuitive procedures based on lottery questions are used to elicit the designer's preference structure: however, they can lead to inconsistent and inexact preference results due to the rank reversal problems derived from the designer's big cognitive burden. In this paper, alternatively, a design methodology based on multiattribute utility function through the pairwise comparison among alternatives is presented. The proposed procedure is applied to an actual injection mold design with the aid of the CAE simulation and the result is discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.4
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• pp.61-68
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• 2002

This paper provides a method of consciousness structure analysis for research and development project evaluation using fuzzy structure modeling(FSM). Fuzzy structure modeling, which is a modeling method for consciousness structure, has a large number of pairwise comparison by human subjective judgement and is difficult to check the consistency index of denoting the precision for human judgement. Thus, in this paper, we analyzed the structure of consciousness by fuzzy structural modeling method, introducing the concept of pairwise comparison matrix in Analytic Hierarchy Process.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.775-785
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• 1997

Robustness rates for repeated measures pairwise multiple comparison procedures were investigated in a split plot design with one between- and one within-subjects factor using untrimmed and trimmed data. Five factors were manipulated in the study: distribution, sphericity, variance-covariance heteroscedasticity, total sample size, and sample size ratio. The Welsch test (W) and the Welsch test on trimmed data $(W_{RT})$ performed better than the other procedures, but had a liberal tendency. The trimmed difference score Bonferroni Procedure $(B_{DT})$ was a good choice in some conditions.

• Journal of Korean Society for Quality Management
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• v.40 no.4
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• pp.589-598
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• 2012

Purpose: Determination of the importance values of quality attributes is very important to integrate the Kano model with QFD. A new method to determine the importance values of quality attributes is proposed. Methods: ASC(Average Satisfaction Coefficient) is proposed in order to determine the importance values of quality attributes. To evaluate the effectiveness of ASC, a case study of modern TV sets is conducted, and the performance of ASC is compared with direct importance evaluation and AHP pairwise comparisons. Results: The result of ASC application is similar with those of direct importance evaluation and AHP pairwise comparison. Conclusion: ASC is an effective instrument to determine the importance values of quality attributes. It doesn't need a cumbersome process like AHP pairwise comparison, and can be calculated using the data for the conventional Kano model.