• 경영과학
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• 제10권2호
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• pp.1-9
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• 1993

This paper shows the application of fuzzy set and nonlinear membership function to linear programming problems in a fuzzy environment. In contrast to typical linear programming problems, the objectives and constraints of the problem in a fuzzy environment are defined imprecisely. This paper describes that fuzzy linear programming models can be formulated using the basic concepts of membership functions and fuzzy sets, and that they can be solved by quadratic programming methods. In a numerical example, a linear programming problem with two constraints and two decision variables is provided to illustrate the solution procedure.

• Korean Journal of Mathematics
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• 제4권1호
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• pp.7-16
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• 1996

The optimization problems with quadratic constraints often appear in various fields such as network flows and computer tomography. In this paper, we propose an algorithm for solving those problems and prove the convergence of the proposed algorithm.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집B
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• pp.144-147
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• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.

• 산업경영시스템학회지
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• 제27권3호
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• pp.7-13
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• 2004

In this paper, machine cell formation problem is discussed. To reflect precisely actual manufacturing situations such as routing sequences, production quantities, and machining (or operation) characteristics, a new network presentation (or the problem is proposed. It is formulated as a simple 0-1 quadratic programming model with linear constraints. Then, the model is converted into a 0-1 integer programming model using a variable transformation technique. Lastly, some computational results are presented.

• Journal of applied mathematics & informatics
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• 제12권1_2호
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• pp.211-218
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• 2003

Let H be a Hilbert space, X be a real Banach space, A : H \longrightarrow X be an operator with D(A) dense in H, G： H \longrightarrow H be positive definite, $\chi$ $\in$ D(A) and b $\in$ H. Consider the quadratic programming problem: QP： Minimize $\frac{1}{2}$〈p, $\chi$〉 + 〈$\chi$, G$\chi$〉 subject to A$\chi$= b In this paper, we obtain an explicit solution to the above problem using generalized inverses.

• 한국경영과학회지
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• 제10권1호
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• pp.9-13
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• 1985

This paper develops a decomposition method for stochastic programming with a block diagonal structure. Here we assume that the right-hand side random vector of each subproblem is differente each other. We first, transform this problem into a master problem, and subproblems in a similar way to Dantizig-Wolfe's Decomposition Princeple, and then solve this master problem by solving subproblems. When we solve a subproblem, we first transform this subproblem to a Deterministic Equivalent Programming (DEF). The form of DEF depends on the type of the random vector of the subproblem. We found the subproblem with finite discrete random vector can be transformed into alinear programming, that with continuous random vector into a convex quadratic programming, and that with random vector of unknown distribution and known mean and variance into a convex nonlinear programming, but the master problem is always a linear programming.

• 대한기계학회논문집
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• 제12권2호
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• pp.185-192
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• 1988

본 논문에서는 접촉문제를 보다 정교하게 수식화 함으로써 효율적인 볼 압입 시험 시뮬레이션 방법을 제시하고 이를 실제에 적용하여 방법의 유용성을 보이고자 한다. 아울러 실험을 병행하여 결과를 비교함으로써 해석결과의 신뢰성을 검토한다.

• International Journal of Control, Automation, and Systems
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• 제4권3호
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• pp.318-324
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• 2006

The mobile manipulator is expected to work in partially defined or unstructured environments. In our global/local approach to path planning, joint trajectories are generated for a desired Cartesian space path, designed by the global path planner. For a local path planner, inverse kinematics for a redundant system is used. Joint displacement limit for the manipulator links is considered in the motion planner. In an event of failure to obtain feasible trajectories, the task cannot be accomplished. At the point of failure, a deviation in the Cartesian space path is obtained and a replanner gives a new path that would achieve the goal position. To calculate the deviation, a nonlinear optimization problem is formulated and solved by standard Sequential Quadratic Programming (SQP) method.

• Structural Engineering and Mechanics
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• 제2권3호
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• pp.295-309
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• 1994

The present paper concerns the mathematical study and the numerical treatment of the problem of semirigid connections in bolted steel column base plates by taking into account the possibility of appearance of separation phenomena on the contact surface under certain loading conditions. In order to obtain a convenient discrete form to simulate the structural behaviour of a steel column base plate, the continuous contact problem is first formulated as a variational inequality problem or, equivalently, as a quadratic programming problem. By applying an appropriate finite element scheme, the discrete problem is formulated as a quadratic optimization problem which expresses, from the standpoint of Mechanics, the principle of minimum potential energy of the semirigid connection at the state of equilibrium. For the numerical treatment of this problem, two effective and easy-to-use solution strategies based on quadratic optimization algorithms are proposed. This technique is illustrated by means of a numerical application.

• 대한전자공학회논문지SD
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• 제43권6호
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• pp.23-29
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• 2006

본 논문에서는 Quadratic Programming(QP)을 이용한 효과적인 광역배치 기법을 제안한다. QP를 이용한 배치 기법의 단점인 셀 밀집 문제를 해결하기 위해 추가적인 힘(additional force)과 Grid Pre-warping 기법을 사용하였다 추가적인 힘은 밀집도에 기반한 값으로 적절한 힘을 구하기 위해 새로운 밀집도 함수를 고안하였다. Grid Pre-warping은 셀 좌표 사이의 상대적인 순서에 따라 셀들을 전체 영역에 재배치하는 기법이다. 새로운 밀집도 함수를 통해 구해진 추가적인 힘과 Pre-warping 기법을 반복적으로 적용하여 셀들이 효과적으로 분산된 광역배치를 얻었다. 이렇게 얻어진 배치를 "middle-down" 방식의 배치기인 Mongre의 초기배치로 적용하여 최종 상세배치 결과를 얻었다 제안하는 기법을 적용한 실험결과, FM 기법을 이용한 광역배치에 비해 향상된 결과를 보였으며, 우수한 배치기로 알려진 FengShui, Dragon과도 비교할만한 결과를 얻었다.