• The Journal of Engineering Geology
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• v.28 no.3
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• pp.367-377
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• 2018

This study introduces a DC resistivity inversion method that incorporates structural and inequality constraints to enhance the resolution of resistivity inversions, and presents sample inversion results with these constraints. In the constrained inversions, a base model is constructed from a layered model through interpretation of other geophysical data. Inversion tests establish that both the structural and inequality constraints produce better resistivity models than the unconstrained inversion. However, the inequality inversion not only reproduces the exact layered structure of the background, it reproduces conductive anomalies at a depth of ~ 10 m when an inexact base model of electrical resistivity is used.

• Journal of the Korean Data and Information Science Society
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• v.6 no.2
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• pp.17-27
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• 1995

We propose a framework for representing and processing uncertain knowledge on the basis of constraint satisfaction. A system of equations and/or inequalities can be considered as a set of constraints that should be solved, and each constraint in the set is transformed into a corresponding logical formula which can be solved through a constraint solving program. Most of rule-based systems, for instance, use a simple probabilistic theory in order to maintain uncertain knowledge, therefore uncertain knowledge can be represented and processed in the constraint satisfaction program quite efficiently.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.155-159
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• 2013

In this paper, a nonlinear matrix inequality problem and a nonlinear optimization problem are proposed for obtaining a structured static output feedback controller. The proposed nonlinear optimization problem has LMI (Linear Matrix Inequality) constraints and a nonlinear objective function. Using the conditional gradient method, the nonlinear optimization problem can be solved. A numerical example shows the effectiveness of the proposed approach.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.339-341
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• 1999

본 논문에서는 연상 메모리 기능을 수행하는 셀룰라 신경망(Cellular Neural Netowork)의 설계를 위한 새로운 방법론을 제안한다. 먼저, 셀룰라 신경망 모델의 기본적 특성들을 소개한 후, 최적 성능을 가지고 이진 원형 패턴들을 저장할 수 있는 셀룰라 신경망 모델의 설계 방법을 제약 조건이 가해진 최적화 문제로 공식화한다. 다음으로 이 문제의 제약 조건을 선형 행렬 부등식(Linear Matrix Inequalities)을 포함하는 부등식의 형태로 변환시킬 수 있음을 관찰한다. 마지막으로 셀룰라 신경망 최적 설계 문제를 내부점 방법(interior point method)에 의해 효율적으로 풀릴 수 있는 일반화된 교유값 문제(Generalized Eigen Value Problem)로 변환하고 설계 예제를 통해 제안된 방법의 유효성을 검증한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.358-358
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• 1995

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.116-123
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the closed loop porblem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and effi- ciently. This algorithm is a hybrid type of using both declarative description (constraint representation) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.61-73
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• 2000

The equilibrium network design problem can be formulated as a mathematical Program with variational inequality constraints. We know this problem may have may multiple local solutions due to its inherent characteristics - Nonlinear Objective function and Nonlinear, Nonconvex constraints. Hence, it is difficult to solve for a globally optimal solution. In this paper, we propose a genetic algorithm to obtain a globa1 optimum among many local optima. A Proposed a1gorithm is compared with 4 different solution algorithms for 1 small test network and 1 real-size network. The results of some computational testing are reported.

• Communications of the Korean Mathematical Society
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• v.18 no.4
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• pp.587-602
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• 2003

본 논문에서는 벡터값을 가지는 함수로 이루어진 벡터 변분 부등식들의 해집합사이의 관계, 미분 불가능한 볼록함수로 이루어진 벡터 볼록 최적화 문제의 해집합들과 볼록함수의 아래미분으로 표현된 벡터 변분부등식의 해집합들과의 관계, 제약집합이 볼록 함수로 구체적으로 주어질 때의 벡터 변분부등식의 해가 될 필요 충분조건, 섭동된 강 단조 벡터 변분부등식의 안정성 결과와 섭동된 벡터 강 볼록 최적화문제에의 적용에 대한 최근 연구 결과를 정리한다.

• Computational Structural Engineering
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• v.11 no.1
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• pp.161-170
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• 1998

A general formulation of the long cylinder tolerance design for the joint structure is here presented. The aim of this paper is to calculate the tolerance of joint by defining tolerance as a kind of uncertainty and to obtain the robustness of the joint structure. It is formulated on the bases of the minimum sensitivity theorem. The objective function is the tolerance sensitivity for the Von-Mises stress. It also took into full account the stress, displacement and weight constraints. PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm is used to solve the constrained nonlinear optimization problem. The finite element analysis is performed with CST(Constant-Strain-Triangle) axisymmetric element. Sensitivities for design variables are calculated by the direct differentiation method. The numerical result is presented for the cylindrical structure where the joint tolerance is treated as random variables.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.463-472
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• 2000

In this paper, we consider the problem of realizing associative memories via cellular neural network(CNN). After introducing qualitative properties of the CNN model, we formulate the synthesis of CNN that can store given binary vectors with optimal performance as a constrained optimization problem. Next, we observe that this problem's constraints can be transformed into simple inequalities involving linear matrix inequalities(LMIs). Finally, we reformulate the synthesis problem as a generalized eigenvalue problem(GEVP), which can be efficiently solved by recently developed interior point methods. Proposed method can be applied to both space varying template CNNs and space-invariant template CNNs. The validity of the proposed approach is illustrated by design examples.