• 한국조명전기설비학회지:조명전기설비
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• 제5권3호
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• pp.78-83
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• 1991

This study proposes a unified method to design toroidal transformer and its optimal design algorithm. This unified design method was derived from the fundamental equation of power on the basis of electromagnetic energy of a core and the definition of three parameters(K1, K2, KW) that influence the form of a core and the ratio of a core and coil. Accordingly this design method condenses the whole data for design of toroidal transformer to a standard variable which is the inner diameter of a core. The minimal cost, weight and volume values of the transformer were computed by means of the algorithm to search the optimal values of the parameters. Furthermore, through the CAD, the efficiency of this unified design method and optimal algorithm proposed in this paper was confirmed.

• 대한조선학회논문집
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• 제54권5호
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• pp.378-386
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• 2017

In this paper, a method is presented for the optimal design of submarine pressure hull structures by taking advantage of genetic algorithm techniques. The objective functions and design constraints in the process of structural optimization are based on the ultimate limit states of hull structures. One of the benefits associated with the utilization of genetic algorithm is that the optimization process can be completed within short generations of design variables for the pressure hull structure model. Applied examples confirm that the proposed method is useful for the optimal design of submarine pressure hull structures. Details of the design procedure with applied examples are documented. The conclusions and insights obtained from the study are summarized.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2009년도 정보통신설비 학술대회
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• pp.36-39
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• 2009

We developed an optimal design interface based on VBA(Visual Basic Application) that takes advantage of API(Application Program Interface) function of commonly used EM analysis software. The developed interface is adopted for an optimal design of a septum in a waveguide tee junction using PSO(Particle Swarm Optimization) algorithm. The objective function of the optimal design is defined by $S_{11}$-parameter of the waveguide tee junction Design variables are established as position of the septum, that are changed to satisfy the design goal Using the developed design interface and PSO algorithm, the objective function converged to the smallest value, showing the validity of the proposed method. The design interface was developed using Microsoft Excel software, enabling easy control of design parameters for user. Also, various analysis parameters can be set in the Excel interface, including waveguide input mode and frequency. After completion of the design, field solutions at user-specified positrons can be extracted to the output files in complex number form.

• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.116-124
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• 1999

In most conventional design optimization of dynamic system, design sensitivities are utilized. However, design sensitivities based optimization method has numbers of drawback. First, computing design sensitivities for dynamic system is mathematically difficult, and almost impossible for many complex problems as well. Second, local optimum is obtained. On the other hand, Genetic Algorithm is the search technique based on the performance of system, not on the design sensitivities. It is the search algorithm based on the mechanics of natural selection and natural genetics. GA search, differing from conventional search techniques, starts with an initial set of random solutions called a population. Each individual in the population is called a chromosome, representing a solution to the problem at hand. The chromosomes evolve through successive iterations, called generations. As the generation is repeated, the fitness values of chromosomes were maximized, and design parameters converge to the optimal. In this study, Genetic Algorithm is applied to the actual dynamic optimization problems, to determine the optimal design parameters of the dynamic system.

• Structural Engineering and Mechanics
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• 제43권6호
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• pp.771-794
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• 2012

This paper presents a multi-objective evolutionary algorithm for combinatorial optimisation and applied for design optimisation of fiber reinforced composite structures. The proposed algorithm closely follows the implementation of Pareto Archive Evolutionary strategy (PAES) proposed in the literature. The modifications suggested include a customized neighbourhood search algorithm in place of mutation operator to improve intensification mechanism and a cross over operator to improve diversification mechanism. Further, an external archive is maintained to collect the historical Pareto optimal solutions. The design constraints are handled in this paper by treating them as additional objectives. Numerical studies have been carried out by solving a hybrid fiber reinforced laminate composite cylindrical shell, stiffened composite cylindrical shell and pressure vessel with varied number of design objectives. The studies presented in this paper clearly indicate that well spread Pareto optimal solutions can be obtained employing the proposed algorithm.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 II
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• pp.1157-1160
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• 2003

We proposed a study on optimal clock period selection algorithm for low power RTL design. The proposed algorithm use the way of maintaining the throughput by reducing supply voltage after improve the system performance in order to minimize the power consumption. In this paper, it select the low power to use pipeline in the transformation of architecture. Also, the algorithm is important the clock period selection in order to maximize the resource sharing. however, it execute the optimal clock period selection algorithm.

• Communications for Statistical Applications and Methods
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• 제7권1호
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• pp.357-370
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• 2000

This study has adapted a genetic algorithm for an optimal design for the first time. the models that was used a simulation are the first and second order response surfaces model, Using an genetic algorithm in D-opimal it is more efficient than previous algorithms to get an object function. Not like other algorithm without any restrictions like troublesome about the initial solution not falling into a local optimal solution it's the most suitable algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1460-1463
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• 1997

The aim of this paper is to suggest a design method of the model following optimal boiler-turbine H.inf. control system using genetic algorithm. This boiler-turbine H.inf. control system is designed by applying genetic algortihm with reference model to the optimal determination of weighting functions and design parameter .gamma. that are given by Glover-Doyle algornithm whch can design H.inf. contrlaaer in the sate. space. The first method to do this is ghat the gains of weightinf functions and .gamma. are optimized simultaneously by genetic algroithm. And the second method is that not only the gains and .gamma. but also the dynamics of weighting functions are optimized at the same time by genetic algonithm. The effectiveness of this boiler-turbine H.inf. control system is verified and compared with LQG/LTR control system by computer simulation.

• 전기학회논문지
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• 제57권1호
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• pp.40-45
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• 2008

This paper presents an optimal design of a permanent magnet actuator(PMA) using a parallel genetic algorithm. Dynamic characteristics of permanent magnet actuator model are analyzed by coupled electromagnetic-mechanical finite element method. Dynamic characteristics of PMA such as holding force, operating time, and peak current are obtained by no load test and compared with the analyzed results by coupled finite element method. The permanent magnet actuator model is optimized using a parallel genetic algorithm. Some design parameters of vertical length of permanent magnet, horizontal length of plunger, and depth of permanent magnet actuator are predefined for an optimal design of permanent magnet actuator model. Furthermore dynamic characteristics of the optimized permanent magnet actuator model are analyzed by coupled finite element method. A displacement of plunger, flowing current of the coil, force of plunger, and velocity of plunger of the optimized permanent magnet actuator model are compared with the results of a primary permanent magnet actuator model.

• 소성∙가공
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• 제5권4호
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• pp.269-280
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• 1996

A new approach to die shape optimal design in extrusion is presented. The approach consists of a FEM analysis model to predict the value of the objective function a design model to relate the die profile with the design variables and a genetic algorithm based optimaization procedure. The approach was described in detail with emphasis on our modified micro genetic algorithm. Comparison with theoretical solutions was made to examine the validity of the predicted optimal die shapes. The approach was then applied to revealing the optimal die shapes with regard to various objective functions including those for which the design sensitivities can not be deter-mined analytically.