• 한국경영과학회지
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• 제25권4호
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• pp.1-14
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• 2000

The methods of sensitivity analysis for linear programming can be classified in two types: sensitivity analysis using an optimal solution, and sensitivity analysis using an approximate optimal solution. As the methods of sensitivity analysis using an optimal solution, there are three sensitivity analysis methods: sensitivity analysis using an optimal basis, positive sensitivity analysis, and optimal partition sensitivity analysis. Since they may provide different characteristic regions under degeneracy, it is not easy to understand and apply the results of the three methods. In this paper, we propose a generalized sensitivity analysis that can integrate the three existing methods of sensitivity analysis. When a right-hand side or a cost coefficient is perturbed, the generalized sensitivity analysis gives different characteristic regions according to the controlling index set that denotes the set of variables allowed to have positive values in optimal solutions to the perturbed problem. We show that the three existing sensitivity analysis methods are special cases of the generalized sensitivity analysis, and present some properties of the generalized sensitivity analysis.

• Management Science and Financial Engineering
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• 제10권2호
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• pp.103-118
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• 2004

$\epsilon$-sensitivity analysis is a kind of methods for performing sensitivity analysis for linear programming. Its main advantage is that it can be directly applied for interior-point methods with a little computation. Although $\epsilon$-sensitivity analysis was proposed several years ago, there have been no studies on its relationship with other sensitivity analysis methods. In this paper, we discuss the relationship between $\epsilon$-sensitivity analysis and sensitivity analysis using an optimal basis. First. we present a property of $\epsilon$-sensitivity analysis, from which we derive a simplified formula for finding the characteristic region of $\epsilon$-sensitivity analysis. Next, using the simplified formula, we examine the relationship between $\epsilon$-sensitivity analysis and sensitivity analysis using optimal basis when an $\epsilon$-optimal solution is sufficiently close to an optimal extreme solution. We show that under primal nondegeneracy or dual non degeneracy of an optimal extreme solution, the characteristic region of $\epsilon$-sensitivity analysis converges to that of sensitivity analysis using an optimal basis. However, for the case of both primal and dual degeneracy, we present an example in which the characteristic region of $\epsilon$-sensitivity analysis is different from that of sensitivity analysis using an optimal basis.

• 산업공학
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• 제7권3호
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• pp.193-199
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• 1994

The purpose of this paper is to develop a method of the sensitivity analysis that can be applicable to a degenerate tree solution of the minimum cost flow problem. First, we introduce two types of sensitivity analysis. A sensitivity analysis of Type 1 is the well known method applicable to a spanning tree solution. However, this method have some difficulties in case of being applied to a degenerate tree solution. So we propose a sensitivity analysis of Type 2 that keeps solutions of upper bounds remaining at upper bounds, those of lower bounds at lower bounds, and those of intermediate values at intermediate values. For the cost coefficient, we present a method that the sensitivity analysis of Type 2 is solved by using the method of a sensitivity analysis of Type 1. Besides we also show that the results of sensitivity analysis of Type 2 are union set of those of Type 1 sensitivity analysis. For the right-hand side constant or the capacity, we present a simple method for the sensitivity analysis of Type 2 which uses arcs with intermediate values.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.543-547
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• 2001

CAE has been settled down to an indispensable tool for the simulation of a mechanical system according to the development of computer-aided analysis rapidly. Particularly finite element programs have advanced to the one of most valuable things in the filed of CAE due to the remarkable progress in the implementation. But since this analysis tool mostly provides the result of the analysis, it cannot satisfy designers who are seeking for information to improve their designs. Therefore, design sensitivity analysis or optimization module has been incorporated into commercial FEA programs to satisfy the desire of designers since 1990s. Design sensitivity analysis is to compute the rate of change of response with respected to design variable. Design sensitivity analysis is classfied into static design sensitivity analysis, Eigenvalue design sensitivity analysis and dynamic design sensitivity analysis. In this research, it will be presented to nonlinear static design sensitivity analysis formulation and nonlinear static design sensitivity analysis external module based ANSYS have been developed and illustrated an example to verify the developed module.

• 한국정밀공학회지
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• 제14권10호
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• pp.164-169
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• 1997

The aim of this paper is to present some results of sensitivity analysis in frequency domain. The sensitivity fonctions in frequency domain is not depend on the external excitation but depend on the frequency of the system's resonance. The sensitivity functions are determined as function of partial derivatives of system transfer functions taken with respect to system design parameters. The logarithmic sensitivity function is the dimensionless sensitivity funciton available, making it useful to compare the influence of various parameters on system variables. Two degree of fredom system is used to illustrate the procedure for sensitivity analysis proposed in this paper.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.492-497
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• 2004

Three methods for design sensitivity such as numerical differentiation, analytical method and semi-analytical method have been developed for the last three decades. Although analytical design sensitivity analysis is exact, it is hard to implement for practical design problems. Therefore, numerical method such as finite difference method is widely used to simply obtain the design sensitivity in most cases. The numerical differentiation is sufficiently accurate and reliable for most linear problems. However, it turns out that the numerical differentiation is inefficient and inaccurate because its computational cost depends on the number of design variables and large numerical errors can be included especially in nonlinear design sensitivity analysis. Thus semi-analytical method is more suitable for complicated design problems. Moreover semi-analytical method is easy to be performed in design procedure, which can be coupled with an analysis solver such as commercial finite element package. In this paper, implementation procedure for the semi-analytical design sensitivity analysis outside of the commercial finite element package is studied and computational technique is proposed, which evaluates the pseudo-load for design sensitivity analysis easily by using the design variation of corresponding internal nodal forces. Errors in semi-analytical design sensitivity analysis are examined and numerical examples are illustrated to confirm the reduction of numerical error considerably.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.508-512
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• 1997

Design sensitivity analysis of Eigen Problem give systematic design improvement information for noise and vibration of a system. Based on reliable results form commercial FE code(UAI/NASTRAN), three computational procedures for design sensitivity analysis of eigen problem are suggested. Those methods are finite difference,design sensitivity analysis using external module and design sensitivity analysis running with NASTRAN. To verify the suggested methods, a numerical example is given and these results are compared with the results from UAI/NASTRAN eigen sensitivity option. We can conclude that design sensitivity coefficient of eigen proplems can be computed outside of the FE code as easy as inside of the FE code.

• 복식문화연구
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• 제15권6호
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• pp.1078-1083
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• 2007

The purpose of this study is to identify the relationships among price sensitivity, brand sensitivity, and fashion innovativeness. The data used in this study were gathered through surveying university students residing in Seoul metropolitan area using convenience sampling method. One hundred thirty eight questionnaires were used in statistical analysis, confirmatory factor analysis and path analysis using structural equation modeling. The results showed that the higher the price sensitivity, the lower the fashion innovativeness and the brand sensitivity.

• 한국경영과학회지
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• 제20권1호
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• pp.1-10
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• 1995

The purpose of this paper is to develop a method of the sensitivity analysis that can be applied to a non-tree solution of the minimum cost flow problem. First, we introduce two types of sensitivity analysis. A sensitivity analysis of Type 1a is the well known method applicable to a tree solution. However this method can not be applied to a non-tree solution. So we propose a sensitivity analysis of Type 2 that keeps solutions of upper bounds at upper bounds, those of lower bounds at lower bounds, and those of intermediate values at intermediate values. For the cost coefficient we present a method that the sensitivity analysis of Type 2 is solved by finding the shortest path. Besides we also show that the results of Type 2 and Type 1 are the same in a spanning tree solution. For the right-hand side constant or the capacity, the sensitivity analysis of Type 2 is solved by a simple calculation using arcs with intermediate values.

• 소음진동
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• 제9권6호
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• pp.1145-1151
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• 1999

Sensitivity analysis and structural modification technique are used to reduce the interior noise of a passenger car. The sensitivity analysis for the noise level at the rear seat shows that the stiffness change at the front lower member and the rear roof rail are sensitive. Using the structural modification method, we verified that the reinforcements at those members decrease the noise transfer function from the body to the rear seat. The combined application of the sensitivity analysis and structural modification method can decrease the noise level effectively.