• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.229-236
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• 2004

This article presents a multiple comparison ranking procedure for several products of the Poisson rates. A preference probability matrix that warrants the optimal comparison ranking is introduced. Using a Bayesian Monte Carlo method, we develop simulation-based procedure to estimate the matrix and obtain the optimal ranking via a row-sum scores method. Necessary theory and two illustrative examples are provided.

• Bulletin of the Korean Mathematical Society
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• v.37 no.3
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• pp.551-568
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• 2000

We propose new parallelizable block incomplete factorization preconditioners for a symmetric block-tridiagonal H-matrix. Theoretical properties of these block preconditioners are compared with those of block incomplete factorization preconditioners for the corresponding comparison matrix. Numerical results of the preconditioned CG(PCG) method using these block preconditioners are compared with those of PCG method using a standard incomplete factorization preconditioner to see the effectiveness of the block incomplete factorization preconditioners.

• Proceedings of the CALSEC Conference
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• 2005.03a
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• pp.130-134
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• 2005

This research describes the comparison broker's role and its effectiveness measurement using a developed logical framework of comparison shopping service. And verifies that seller-led comparison challenge method provide comparison information of products to buyers more efficiently. In electronic commerce, buyer's satisfaction of purchase (S) can be defined as an interactive function between seller's competitiveness vector (P) of products that supplied to the market, and buyer's informed level vector (B) of products that is known from a lot of sources. Then the buyer's informed level can be changed through the information analysis among products by transformation process using comparison matrix (C). So the role of comparison shopping is to construct a comparison matrix and to serve it to the buyers, and to change the buyer's informed level. The changed informed level influences a buyer's satisfaction, that improved satisfaction of purchase is defined as the effectiveness of comparison shopping. As a perfect provision and usage of comparison matrix is impossible cause of cognitive limit, the most efficient method for improving the comparison effectiveness is the comparison challenge that detects the comparison elements of the largest buyer's information efficiency, and then to be compared between elementary products selectively. This research verifies the substantial superiority of comparison challenge through television market data experiments.

• Communications of the Korean Mathematical Society
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• v.27 no.1
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• pp.207-215
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• 2012

In this paper, we provide comparison results of several types of the preconditioned Gauss-Seidel methods for solving a linear system whose coefficient matrix is a Z-matrix. Lastly, numerical results are presented to illustrate the theoretical results.

• Communications of the Korean Mathematical Society
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• v.34 no.2
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• pp.657-670
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• 2019

In this paper, we consider the preconditioned iterative methods for solving linear complementarity problem associated with an M-matrix. Based on the generalized Gunawardena's preconditioner, two preconditioned SSOR methods for solving the linear complementarity problem are proposed. The convergence of the proposed methods are analyzed, and the comparison results are derived. The comparison results showed that preconditioned SSOR methods accelerate the convergent rate of the original SSOR method. Numerical examples are used to illustrate the theoretical results.

• 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.

• 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.

• 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.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.291-301
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• 2011

This research describes the comparison broker's role and its effectiveness measurement framework of comparison shopping. We verified seller-led comparison challenge method provide comparison information of products to buyers more efficiently. Buyer's satisfaction of purchase (S) can be defined as an interactive function between seller's competitiveness vector (P) of products that supplied to the market, and buyer's informed level vector (B) of products that is known from a lot of sources. Then the buyer's informed level can be changed through the information analysis among products by transformation process using comparison matrix (C). So the role of comparison shopping is to construct a comparison matrix and to serve it to the buyers, and to change the buyer's informed level. The changed informed level influences a buyer's satisfaction, that improved satisfaction of purchase is defined as the effectiveness of comparison shopping. As a perfect construction and usage of comparison matrix is impossible, a more efficient method for improving the comparison effectiveness is the comparison challenge. This research shows that comparison shopping makes 9.32% and comparison challenge makes 19.11% enhancement of comparison effectiveness through television market data experiments.

• 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.