• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.2
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• pp.131-138
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• 2009

Analytical modal verification is considered as the process to provide an acceptable description of the subject structure's behaviour. In general, results of original analytical model are different with actual structure results to uncertainty like non-linearity of material, boundary and modified shape, etc. In this paper, the dynamic model of glider's wing is correlated with static deformation and vibration test results by goal-attainment method, multi-objects optimization technique. The structural responses are predicted by using finite element method and optimization is carried out by using the SQP(sequential quadratic programming) method which is widely used in the constrained nonlinear optimization problem. The MAC(Modal Assurance Criterion) is used to modify the mode shapes and quantify the similarity.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.6
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• pp.555-562
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• 2016

Seismic design of braced frames that simultaneously considers economic issues and structural performance represents a rather complicated engineering problem, and therefore, a systematic and well-established methodology is needed. This study proposes a multi-objective seismic design method for an inverted V-braced frame with suspended zipper struts that uses the non-dominated sorting genetic algorithm-II(NSGA-II). The structural weight and the maximum inter-story drift ratio as the objective functions are simultaneously minimized to optimize the cost and seismic performance of the structure. To investigate which of strength- and performance-based design criteria for braced frames is the critical design condition, the constraint conditions on the two design methods are simultaneously considered (i.e. the constraint conditions based on the strength and plastic deformation of members). The linear static analysis method and the nonlinear static analysis method are adopted to check the strength- and plastic deformation-based design constraints, respectively. The proposed optimal method are applied to three- and six-story steel frame examples, and the solutions improved for the considered objective functions were found.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.17-34
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• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.293-307
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• 2004

We consider the problem of scheduling tasks of a precedence constrained task graph, where each task has its execution time and deadline, onto a set of identical processors in a way that simultaneously minimizes the number of processors required and the total tardiness of tasks. Most existing approaches tend to focus on the minimization of the total tardiness of tasks. In another methods, solutions to this problem are usually computed by combining the two objectives into a simple criterion to be optimized. In this paper, the minimization is carried out using a multiobjective genetic algorithm (GA) that independently considers both criteria by using a vector-valued cost function. We present various GA components that are well suited to the problem of task scheduling, such as a non-trivial encoding strategy. a domination-based selection operator, and a heuristic crossover operator We also provide three local improvement heuristics that facilitate the fast convergence of GA's. The experimental results showed that when compared to five methods used previously, such as list-scheduling algorithms and a specific genetic algorithm, the Performance of our algorithm was comparable or better for 178 out of 180 randomly generated task graphs.

• 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.

• Annual Conference of KIPS
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• 2008.11a
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• pp.17-18
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• 2008

다변량 퍼지 의사결정트리(이하 MFDT)는 학습 모델의 구조가 간소하고 분류율이 높다는 장점 때문에 일반 퍼지 의사결정트리를 대신해 손동작 인식 시스템의 분류기로 사용되었다. 다양한 사용자의 손동작 특성을 분류하기 위해 여러 개의 인식 모델을 만들고 새로운 사용자에게 가장 적합한 모델을 선택해 사용하는 모델 선택 기법도 손동작 인식에 적용되었다. 모델 선택 과정을 통해 선택된 모델은 기존 모델 중에서 새로운 사용자의 특성에 가장 가깝지만 해당 사용자에 최적화된 모델이라고는 할 수 없다. 이 논문에서는 MFDT 모델을 새로 입력된 데이터를 이용해 적응시키는 방법을 설명하고 실험 결과를 통해 적응 성능을 검증한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.144-151
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• 2003

In this paper, an optimum design problem for endosseous implant in dentistry is studied to find best implant design. An optimum design problem is formulated to reduce stresses arising at the cortical as well as cancellous bones, in which sufficient design parameters are chosen fur design definition that encompasses major implants in popular use. Optimization at once (OAO) with the large number of design variables, however, causes too costly solution or even failure to converge. A concept of multilevel optimization (MLO) is employed to this end, which is to group the design variables of similar nature, solve the sub-problem of smaller size fur each group in sequence, and this is iterated until convergence. Each sub-problem is solved based on the response surface method (RSM) due to its efficiency for small sized problem. Favorable solution is obtained by the MLO, which is compared to both solutions made by RSM and sequential quadratic programming (SQP) in the OAO problem.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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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.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.3
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• pp.154-164
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• 1994

In this study, to find an economical production method which yields welded built-up beams with high quality, simulation techniques and optimization method are used. At first, fabrication variables such as welding current, voltage and speed and heated depth and breadth are selected and fabrication cost of a built-up beam is expressed by these parameters, which is optimized under the constraints. As advanced studies, total production cost including the fabrication cost and the material cost of the beam is expressed by the fabrication and design variables, and optimized with the design constraints by the class rules. In addition, assuming that heating for straightening is impossible. the optimization method of multi-objective functions based on the weighting method is applied to obtain the compromised optimal solutions of the total production cost and the welding deformation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1793-1803
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• 2010

The weighting method and goal programming require weighting factors or target values to obtain a Pareto optimal solution. However, it is difficult to define these parameters, and a Pareto solution is not guaranteed when the choice of the parameters is incorrect. Recently, the Mahalanobis Taguchi System (MTS) has been introduced to minimize the Mahalanobis distance (MD). However, the MTS method cannot obtain a Pareto optimal solution. We propose a function called the skewed Mahalanobis distance (SMD) to obtain a Pareto optimal solution while retaining the advantages of the MD. The SMD is a new distance scale that multiplies the skewed value of a design point by the MD. The weighting factors are automatically reflected when the SMD is calculated. The SMD always gives a unique Pareto optimal solution. To verify the efficiency of the SMD, we present two numerical examples and show that the SMD can obtain a unique Pareto optimal solution without any additional information.