• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.565-571
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• 2001

As a method of structural optimization, a practical algorithm based on the Taguchi method is developed. The Taguchi method is applied iteratively updating the level values of design variables. The design region is translated or reduced during optimization and by appropriate choice of reduction factor and initial level intervals, a near-optimum solution can be found very efficiently. To treat inequality constraints, a variable penalty method is utilized. A software system named 'DS/Taguchi' is developed by integrating the proposed algorithm and commercial finite element analysis codes on the parametric CAD platform. Two examples are taken to examine the performance of the proposed algorithm and the developed software system.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.195-202
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• 1999

본 논문은 배전 계통에서 부하 제약조건과 운전 제약조건을 고려한 손실 감소와 부하 평형에 대해 시뮬레이티드 어닐링 알고리즘을 적용한 재구성 방법을 서술하였다. 네트워크 재구성은 수많은 연계 개폐기와 구분 계폐기의 조합에 의해 이루어지기 때문에 조합적인 최적화 문제이다. 이러한 문제는 수많은 조합에 제약조건까지 있어 해를 구하기가 쉽지 않을뿐 아니라 국소 해에 빠질 가능성이 많다. 따라서 신경망 중에서 제약조건에 따라 신경망 구조에 영향을 미치지 않으면서 전역 최소해에 수렴하는 특성을 가진 시뮬레이티드 어닐링 기법을 이용하여 배전 계통의 선로를 재구성하였다. 시뮬레이티드 어닐링은 이론적으로 최적해가 보장되지만 무한대의 시간이 걸리기 때문에 현실적으로 적용할 때 해 공간을 탐색하는 규칙과 온도를 적절히 내리는 냉각 스케줄(cooling schedule)이 중요하다. 본 논문에서는 알고리즘 상에서 제약조건 위한 여부를 점검할 수 있는 제약조건과 페널티 상수(penalty factor)를 통해 목적함수에 반영하는 제약조건으로 나누어 모든 후보해를 가능해가 되게 하였고 기존에 사용되는 Kirkpatrick의 냉각 스케줄 대신에 후보해의 통계적 처리에 의해 온도를 내리는 다항-시간 냉각 스케줄(polynomial-time schedule)을 사용하여 수행시간을 단축하고 수렴성을 높였다. 제안한 알고리즘의 효용성을 입증하기 위해 32,69모선 예제 계통으로 테스트하였다.

• Journal of Mechanical Science and Technology
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• 제14권3호
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• pp.306-313
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• 2000

The homogenization method and the density function method are common approaches to evaluate the equivalent material properties for design cells composed of matter and void. In this research, using a new topology optimization method based on the homogenized material with a penalty factor and the chessboard prevention strategy, we obtain the optimal layout of a structure for the natural frequency of a designated mode. The volume fraction of nodes of each finite element is chosen as the design variable and a total material usage constraint is imposed. In this paper, the subspace method is used to evaluate the eigenvalue and its corresponding eigenvector of the structure for the designated mode and the recursive quadratic programming algorithm, PLBA algorithm, is used to solve the topology optimization problem.

• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.457-469
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• 2007

Process Capability Indexes(PCI) are used as the measure for evaluation of process capability analysis and is the statistical method for efficient process control. The fourth generation $PCI(C_{psk})$ is constructed from $C_{pmk}$ by introducing the factor $\mid\mu-T\mid$ in the numerator as an extra penalty for the departure of the process mean from the preassigned target value T And Process Incapability Indexes(PII) are presented by inversing PCI and include the information of PCI. This paper introduces the PII $C_{ss}^*$ provide manager with various information of process and include Gage R&R. PII $C_{ss}^*$ is presented by inversing PCI $C_{psk}$ and include the information of PCI $C_{psk}$.

• JSTS:Journal of Semiconductor Technology and Science
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• 제9권3호
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• pp.148-152
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• 2009

Recent CMOS technology scaling has seriously eroded the bit-line noise immunity of register files due to the consequent increase in active bit-line leakage currents. To restore its noise immunity while maintaining performance, we propose and evaluate a $256{\times}40$-bit register file incorporating dual-$V_t$ bit-lines with a boosted gate overdrive voltage in 65 nm bulk CMOS technology. Simulation results show that the proposed bootsrapping scheme lowers leakage current by a factor of 450 without its performance penalty.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.484-484
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• 2000

The problem of determining the proper size of an neural network is recognized to be crucial, especially for its practical implications in such important issues as learning and generalization. Unfortunately, it usually is not obvious what size is best: a system that is too snail will not be able to learn the data while one that is just big enough may learn the slowly and be very sensitive to initial conditions and learning parameters. One popular technique is commonly known as pruning and consists of training a larger than necessary network and then removing unnecessary weights/nodes. In this paper, a new pruning method is developed, based on the penalty-term methods. This method makes the neural network good for the generalization and reduces the retraining time after pruning weights/nodes.

• 한국공작기계학회논문집
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• 제18권1호
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• pp.103-109
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• 2009

This paper presents structural design optimization of a micro milling machine for minimum weight and compliance using a genetic algorithm with dynamic penalty function. The optimization procedure consists of two design stages, which are the static and dynamic design optimization stages. The design problem, in this study, is to find out thickness of structural members which minimize the weight, the static compliance and the dynamic compliance of the micro milling machine under several constraints such as dimensional constraints, maximum compliance limit, and safety factor criterion. Optimization results showed a great reduction in the static and dynamic compliances at the spindle nose of the micro milling machine in spite of a little decrease in the machine weight.

• 대한조선학회지
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• 제21권2호
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• pp.1-7
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• 1984

This paper is concerned with an optimum design study of containerships in preliminary stage by applying economic criteria. The Net Present Value Index (NPVI) and the Required Freight Rate(RFR) are used as measures of merit. Hooke & Jeeves direct search method and External Penalty Function method of Sequential Unconstrained Minimization Techniques(SUMT) are used for solving constrained nonlinear optimization problem. Sensitivity analysis is carried out to investigate the effect on the optimum solution due to change of values in some parameters such as crane capacity, load factor, oil price, ship speed and the ratio between loaded FEU and TEU.

• 대한전기학회논문지:전력기술부문A
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• 제48권4호
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• pp.371-378
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• 1999

This paper presents an efficient algorithm for loss reduction of distribution system by automatic sectionalizing switch operation in large scale distribution systems of radial type. Simulated Annealing algorithm among optimization techniques can avoid escape from local minima by accepting improvements in cost, but the use of this algorithm is also responsible for an excessive computation time requirement. To overcome this major limitation of Simulated Annealing algorithm, we may use advanced Simulated Annealing algorithm. All constaints are divided into two constraint group by using perturbation mechanism and penalty factor, so all trail solutions are feasible. The polynomial-time cooling schedule is used which is based on the statistics calculation during the search. This approaches results in saving CPU time. Numerical examples demonstrate the validity and effectiveness of the proposed methodology.

• 전기학회논문지
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• 제57권4호
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• pp.560-566
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• 2008

Today, as the power trades between generation companies and power customer are liberalized, the uncertainty level of operated power system is rapidly increased. Therefore, transmission operators as decision makers for transmission expansion are required to establish a deliberate investment plan for effective operations of transmission facilities considering forecasted conditions of power system. This paper proposes the methodology for the optimal solution of transmission expansion in deregulated power system. The paper obtains the expected value of transmission congestion cost for various scenarios by using occurrence probability. In addition, the paper assumes that increasing rates of loads are the probability distribution and indicates the location of expanded transmission line, the time for transmission expansion with the minimum cost for the future by performing the Montecarlo simulation. To minimize the investment risk as the variance of the congestion cost, Mean-Variance Markowitz portfolio theory is applied to the optimization model by the penalty factor of the variance. By the case study, the optimal solution for transmission expansion plan considering the feature of market participants is obtained.