• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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• pp.209-216
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• 2005

The controller that can control the smart base isolation system consisting of M damper and friction pendulum systems(FPS) is developed in this study. A fuzzy logic controller (FLC) is used to modulate the M damper force because the FLC has an inherent robustness and ability to handle non-linearities and uncertainties. A genetic algorithm (GA) is used for optimization of the FLC. When earthquake excitations are applied to the structures equipped with smart base isolation system, the relative displacement at the isolation level as well as the acceleration of the structure should be regulated under appropriate level. Thus, NSGA-II(Non-dominated Sorting Genetic Algorithm) is employed in this study as a multi-objective genetic algorithm to meet more than two control objectives, simultaneously. NSGA-II is used to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can efficiently find Pareto optimal sets that can reduce both structural acceleration and base drift from numerical studies.

• 한국기계가공학회지
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• 제15권3호
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• pp.8-14
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• 2016

Medical bed head consoles (BHC) are generally used to increase the efficiency of medical equipment and speed the medical treatment response time. The BHC design has been consistently improved including a movable shelf unit that is embedded to mount stably medical instruments on the lower part of the main console. The cost of a BHC can be reduced through design optimization to limit the overall weight. However, as the size of a head console might decrease due to design optimization, the BHC deflection could be increased. In this study, multi-objective optimal design was adopted to consider this BHC design problem. In order to reduce the cost of optimization planning, an approximate model was applied for the design optimization. In the context of approximate optimization, we used the response surface method and non-dominant sorting genetic algorithm developed from various fields. Multi-objective optimal solutions were also compared with a single objective optimal design.

• Journal of Computational Design and Engineering
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• 제1권4호
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• pp.256-265
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• 2014

Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

• 한국정밀공학회지
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• 제32권9호
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• pp.815-824
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• 2015

In this study, we conducted the approximate multi-objective optimization of gap sizes of pressurized-water reactor (PWR) annular fuels. To determine the contacting tendency of the inner-outer gaps between the annular fuel pellets and cladding, thermoelastic-plastic-creep (TEPC)analysis of PWR annular fuels was performed, using in-house FE code. For the efficient heat transfer at certain levels of stress, we investigated the tensile, compressive hoop stress and temperature, and optimized the gap sizes using the non-dominant sorting genetic algorithm (NSGA-II). For this, response surface models of objective and constraint functions were generated, using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by NSGA-II were verified through the TEPC analysis, and we compared the obtained optimum solutions and generated errors from the CCD and D-optimal design. We observed that optimum solutions differ, according to design of experiments (DOE) method.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.292-296
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• 2010

본 연구에서는 상대적으로 소규모 홍수저감시설인 천변저류지의 설치를 통하여 대규모 유역 하도 전체에서의 홍수위 저감효과를 평가하고 그 효율을 극대화 하는 방안을 제시하였다. 본 연구에 적용한 다목적 최적화 기법(Multi-objective Optimization)으로는 NSGA-II(Non-dominated Sorting Genetic Algorithm II) 알고리즘을 적용하였으며 천변저류지 설치에 따른 수위 영향구간 분석 및 유역 전체 하도구간에서 전반적으로 발생하는 수리, 수문학적인 변화 평가 및 천변저류지 최적 조합을 선정하기 위하여 천변저류지의 용량을 최소화하면서 하도 전 구간에서의 수위 저감량을 최대화할 수 있도록 최적화 알고리즘의 목적함수를 설정하였다. 천변저류지 설치에 따른 홍수량의 변화를 해석하기 위하여 안성천 유역에 대하여 동역학적 홍수추적을 수행하였으며 저류형 구조물의 설치에 따른 홍수량 저감효과 및 그에 따른 홍수위의 변화를 동시에 해석하기 위하여 UNET 모형을 기반으로 한 HEC-RAS 부정류 해석을 실시하였다. 천변저류지 조합별로 다양한 경우의 수가 존재하므로 HEC-RAS 구동 모듈인 HECRAS Controller를 Visual Basic으로 코딩된 최적화 알고리즘 프로그램과 연동함으로써 각 경우의 수별로 동역학적 홍수추적 및 부정류 해석을 실시함으로써 천변저류지 조합별 각 측점에서의 홍수량 및 홍수위를 산정하여 저류지 용량을 최소화하면서 각 하도 측점별 수위저감량을 최대화 하는 최적해 집단(Pareto Front)을 산정하여 제시하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 춘계학술대회
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• pp.699-701
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• 2010

해상 감시용 Multi Sensor 및 IFOG 개발을 위하여 주 야간 겸용 감시카메라의 통합 개발과 시스템 Control Unit 설계 및 항해 장비 연동 시스템 제작하였다. 선박 통합 시스템의 Control Unit의 분석은 Control Unit에 연결 가능한 항해 장비 리스트를 선별하는 것으로 시작 하였다. 항해 장비 리스트를 선별한 후 각 항해 장비의 용도와 특성, 연결 방법, 통신 방법, 데이터 종류에 따라 Control Unit와 항해 장비간의 데이터 방향성, 데이터 종류들을 선별하여 그 성능을 보여주었다.

• International Journal of Air-Conditioning and Refrigeration
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• 제16권1호
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• pp.1-8
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• 2008

Numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm(NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis is presented in this work. Reynolds-averaged Navier-Stokes(RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3501-3523
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• 2017

It is a classical integer optimization difficulty to design an optimal selection scheme in cooperative relay networks considering co-channel interference (CCI). In this paper, we solve single-objective and multi-objective relay selection problem. For the single-objective relay selection problem, in order to attain optimal system performance of cooperative relay network, a novel quantum differential evolutionary algorithm (QDEA) is proposed to resolve the optimization difficulty of optimal relay selection, and the proposed optimal relay selection scheme is called as optimal relay selection based on quantum differential evolutionary algorithm (QDEA). The proposed QDEA combines the advantages of quantum computing theory and differential evolutionary algorithm (DEA) to improve exploring and exploiting potency of DEA. So QDEA has the capability to find the optimal relay selection scheme in cooperative relay networks. For the multi-objective relay selection problem, we propose a novel non-dominated sorting quantum differential evolutionary algorithm (NSQDEA) to solve the relay selection problem which considers two objectives. Simulation results indicate that the proposed relay selection scheme based on QDEA is superior to other intelligent relay selection schemes based on differential evolutionary algorithm, artificial bee colony optimization and quantum bee colony optimization in terms of convergence speed and accuracy for the single-objective relay selection problem. Meanwhile, the simulation results also show that the proposed relay selection scheme based on NSQDEA has a good performance on multi-objective relay selection.

• 대한전자공학회논문지SP
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• 제44권2호
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• pp.108-115
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• 2007

본 논문에서는 최적화 알고리즘의 속도를 향상시킬 수 있는 방안으로 설계자가 원하는 목적함수들의 수렴 범위를 Goal로 설정하여 최적화를 수행하는 GBNSGA(Goal-Pareto based Non-dominated Sorting Genetic Algorithm)를 제안한다. 많은 공학문제들은 하나의 목표치를 충족하는 해를 찾는 것이 아니라 다수 목적함수들을 충족하는 해를 찾는 것이 일반적이다 특히, 이러한 목적함수들은 서로 상충적인 관계를 갖는 경우가 대부분이기 때문에 모든 목적함수들을 만족하는 유일해를 찾는 것은 거의 불가능하다. 그 대안으로 일부 목적을 희생하며 설계에 부합되는 최적해를 찾는 파레토(Pareto) 방식의 최적화 알고리즘들에 대한 많은 연구가 진행되었다. 본 논문에서는 이러한 파레토 기반의 최적화 알고리즘들의 성능 향상을 도모하기 위하여 설계자의 목적을 파레토 할당에 반영하는 GBNSGA를 제안하고, 그 성능을 NSGA와 weighted-sum 접근 방식과의 비교를 통해 그 우수성을 검증하였다.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2009년도 추계학술발표논문집
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• pp.645-648
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• 2009

본 논문에서는 안테나 설계에 있어서 자동화 설계 프로세스를 제안하고자 한다. 안테나 설계는 최적화를 위한 반복적인 시뮬레이션 과정을 거쳐야 하며, 설계된 안테나의 실제 적용 시 튜닝 과정을 통한 시간이 많이 소요되는 경우가 있다. 본 논문에서는 유전자 알고리즘을 이용 하여 초기 안테나 모델 설계 시 안테나 설계자에게 사용 가능한 다양한 모델을 제시하며, 안테나 설계 시 중요 인자를 제시함으로써 초기 설계 및 방향설정의 시간을 줄이고자 한다. 사용된 최적화 알고리즘은 Non-dominated Sorting 유전자 알고리즘이며, 이 알고리즘은 multi-objective를 가지는 문제 해결에 적합한 알고리즘이다. 안테나 설계를 위한 EM computational tool로는 ESP V.5가 사용되었다. 시뮬레이션 결과를 통해 사용 가능한 적합한 안테나 모델을 제시하였다.