• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.869-874
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• 2007

In searching for solutions to multiobjective optimization problem, we find that there is no single optimal solution but rather a set of solutions known as 'Pareto optimal set'. To find approximation of ideal pareto optimal set, search capability of diverse individuals at population space can determine the performance of evolutionary algorithms. This paper propose the method to maintain population diversify and to find non-dominated alternatives in Game model based Co-Evolutionary Algorithm.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.333-336
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• 2016

본 연구에서는 개체명 인식의 성능을 향상시키기 위해, 가중 투표 방법을 이용하여 개체명 인식 모델을 앙상블 하는 방법을 제안한다. 각 모델은 Conditional Random Fields의 변형 알고리즘을 사용하여 학습하고, 모델들의 가중치는 다목적 함수 최적화 기법인 NSGA-II 알고리즘으로 학습한다. 실험 결과 제안 시스템은 $F_1Score$기준으로 87.62%의 성능을 보여, 단독 모델 중 가장 높은 성능을 보인 방법보다 2.15%p 성능이 향상되었다.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.4
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• pp.409-416
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• 2009

The structural design problems are acknowledged to be commonly multi-criteria in nature. The various multi-criteria optimization methods are reviewed and the most efficient and easy-to-use Pareto optimal solution methods are applied to structural optimization of a truss and a beam. The result of the study shows that Pareto optimal solution methods can easily be applied to structural optimization with multiple objectives, and the designer can have a choice from those Pareto optimal solutions to meet an appropriate design environment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.39-46
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• 2017

In this paper, a model updating procedure based on the response surface method combined with the multi-objective optimization was proposed and applied for updating of the FE models representing a low-rise reinforced concrete building before and after the seismic retrofit. The dynamic properties to be matched were obtained from vibration tests using a small shaker system. By varying the structural parameters according to the central composite design, analysis results from the initial FE model using a commercial software were collected and used to produce two regression functions each of which representing the errors in the natural frequencies and mode shapes. The two functions were used as the objective functions for multi-objective optimization. Final solution was determined by examining the Pareto solutions with one iteration. The parameters representing the stiffnesses of existing concrete, masonry, connection stiffness in expansion joint, new concrete, retrofitted members with steel section jacketing were selected and identified.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1211-1218
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• 2008

This study is for design of the detention system distributed in a watershed by the Multi-Objective Genetic Algorithms(MOGAs). A new model is developed to determine optimal size and location of detention. The developed model has two primary interfaced components such as a rainfall runoff model to simulate water surface elevation(or flowrate) and MOGAs to get the optimal solution. The objective functions used in this model depend on the peak flow and storage of detention. With various constraints such as structural limitations, capacities of storage and operational targets. The developed model is applied at Gwanyang basin within Anyang watershed. The simulation results show the maximum outlet reduction is occurred at detention facilities located in upper reach of watershed in the peak discharge rates. It is also reviewed the simultaneous construction of an off-line detention and an on-line detention. The methodologies obtained from this study will be used to control the flood discharges and to reduce flood damage in urbanized watershed.

• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.35-48
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• 2019

Domestic hydraulic drifters till now have been developed by benchmarking products from overseas leading companies. However, they do not have excellent impact performance as they are not suitable for characteristics (large flow rate and low pressure) of Korean hydraulic drill power pack, and therefore, research on the optimum design has not made much headway. This study performs multi-objective function optimization for hydraulic drifters whose capacity has been redesigned to deal with the large flow rate, and also with the help of this function, it aims to improve impact power and reduce supply and surge pressure. A summary of the research study is as follows: First, we set goals for improving impact power, supply pressure, and surge pressure, and then perform multi-objective function optimization on them. After that, we secure the reliability of the optimized analytical model by comparing the test results of the prototype built by the optimized design with the analysis results of the analytical model. This study used SimulationX, that is the hydraulic system analysis software, and EasyDesign, which is a multi-objective function optimization program. Through this research, we have achieved the results that satisfy the goal of developing high power drifters suitable for Korean type hydraulic drills.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.7
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• pp.509-515
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• 2013

In this study, the real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was developed for an airfoil shape design. In order to achieve the better aerodynamic characteristics than reference airfoil at landing and cruise conditions, maximum lift coefficient and lift-to-drag ratio were chosen as object functions. Futhermore, the PARSEC method reflecting geometrical properties of airfoil was adopted to generate airfoil shapes. Finally, two airfoils, which show better aerodynamic characteristics than a reference airfoil, were chosen. As a result, maximum lift coefficient and lift-to-drag ratio were increased of 4.89% and 5.38% for first candidate airfoil and 7.13% and 4.33% for second candidate airfoil.

• Journal of Korean Society of Steel Construction
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• v.14 no.3
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• pp.395-402
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• 2002

This study proposed a muti-objective optimum design method for rational optimizing of orthotropic steel deck bridges. This multi-objective optimum design method was found to be effective in optimizing multi-objective problems, considering cost and deflection functions. It may ve difficult to optimize orthotropic steel deck bridges using a conventional optimization, since the bridges have several parts and show complex structural behaviors. Therefore, the Pareto curve can be obtained by performing the multi-objective optimization for real orthotropic steel deck bridges, using the multi-level technique with excellent efficiency. A reasonable and economical design can be attained using the Parato curve in the cost and deflection functions of the bridge. Thus, more reasonable design values can be determined based on a comparison with those using a conventional design procedure.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.113-113
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• 2018

본 연구는 다목적 입자군집최적화(Particle Swarm Optimization, PSO) 알고리즘을 SWAT(Soil and Water Assessment Tool) 모형에 적용하여 자동보정 알고리즘의 적용 가능성을 평가하고자 한다. PSO 알고리즘은 Python을 활용해 다목적 함수를 고려할 수 있도록 새롭게 개발되었다. SWAT 모형의 유출 해석은 안성천의 공도 수위 관측소 상류유역($366.5km^2$)을 대상으로 하였으며, 공도 지점의 2000년부터 2017년까지의 일 유량 자료를 이용하여 검보정하였다. 모형을 위한 기상자료는 공도유역 주변 3개 기상관측소(수원, 천안, 이천)의 일별 강수량, 최고 및 최저기온, 평균 풍속, 상대습도 및 일사량을 구축하였다. SWAT 모형의 유출 해석은 결정계수(Coefficient of determination, $R^2$), RMSE(Root mean square error), Nash-Sutcliffe 모형효율계수(NSE) 및 IOA(index of agreement) 등을 활용하여, 기존 연구 결과와 PSO 알고리즘을 활용한 결과를 비교 분석하고자 한다. 본 연구에서 개발한 다목적 PSO 알고리즘을 활용한 SWAT모형의 유출 해석은 보다 높은 정확도를 얻을 수 있을 것으로 예상되며, Python으로 개발되어 SWAT모형 이외에도 널리 적용될 수 있을 것으로 판단된다.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.1
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• pp.1-11
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• 2021

POGO is a dynamic axial instability phenomenon that occurs in liquid-propelled rockets. As the natural frequencies of the fuselage and those of the propellant supply system become closer, the entire system will become unstable. To predict POGO, the propellant (oxidant and fuel) tank in the first stage is modeled as a shell element, and the remaining components, the engine and the upper part, are modeled as mass-spring, and structural analysis is performed. The transmission line model is used to predict the pressure and flow perturbation of the propellant supply system. In this paper, the closed-loop transfer function is constructed by integrating the fuselage structure and fluid modeling as described above. The pogo suppressor consists of a branch pipe and an accumulator that absorbs pressure fluctuations in a passive manner and is located in the middle of the propellant supply system. The design parameters for its design optimization to suppress the decay phenomenon are set as the diameter, length of the branch pipe, and accumulator. Multiple-objective function optimization is performed by setting the energy minimization of the closed loop transfer function in terms of to the mass of the pogo suppressor and that of the propellant as the objective function.