Comparison of Automatic Calibration for a Tank Model with Optimization Methods and Objective Functions

( Kang Min Goo ),( Park Seung Woo ),( Park Chang Eun ) 한국농공학회 2002 韓國農工學會誌 : 전원과 자원 Vol.44 No.7

Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

단체법에서의 초기기저 구성에 관한 연구

서용원,김우제,박순달 한국경영과학회 1996 經營 科學 Vol.13 No.3

Constructing an initial basis is an important process in the simplex method. An initial basis greatly affects the number of iterations and the execution time in the simplex method. The purpose of this paper is to construct a good initial basis. First, to avoid linear dependency among the chosen columns, an enhanced Gaussian elimination method and a method using non-duplicated nonzero elements are developed. Second, for an order to choose variables, the sparsity of the column is used. Experimental results show that the proposed method can reduce the number of iterations and the execution time compared with Bixby's method by 12%.

FE model updating based on hybrid genetic algorithm and its verification on numerical bridge model

정대성,김철영 국제구조공학회 2009 Structural Engineering and Mechanics, An Int'l Jou Vol.32 No.5

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead’s Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

FE model updating based on hybrid genetic algorithm and its verification on numerical bridge model

Jung, Dae-Sung,Kim, Chul-Young Techno-Press 2009 Structural Engineering and Mechanics, An Int'l Jou Vol.32 No.5

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

Shape Optimization for Interior Permanent Magnet Motor based on Hybrid Algorithm

Yim, Woo-Gyong,An, Kwang-Ok,Seo, Jang-Ho,Kim, Min-Jae,Jung, Hyun-Kyo The Korean Institute of Electrical Engineers 2012 Journal of Electrical Engineering & Technology Vol.7 No.1

In this paper, a design method for minimizing the cogging torque of an Interior Permanent Magnet Motor (IPM) is proposed based on a hybrid algorithm. The suggested optimization algorithm is based on a combination of the Response Surface Method (RSM) and Simplex Method. The results show that the proposed method provides improved characteristics compared to the conventional methods, such as a shorter calculation time and the acquisition of a more correct solution.

Shape Optimization for Interior Permanent Magnet Motor based on Hybrid Algorithm

Woo-Gyong Yim,Kwang-Ok An,Jang-Ho Seo,Min-Jae Kim,Hyun-Kyo Jung 대한전기학회 2012 Journal of Electrical Engineering & Technology Vol.7 No.1

In this paper, a design method for minimizing the cogging torque of an Interior Permanent Magnet Motor (IPM) is proposed based on a hybrid algorithm. The suggested optimization algorithm is based on a combination of the Response Surface Method (RSM) and Simplex Method. The results show that the proposed method provides improved characteristics compared to the conventional methods, such as a shorter calculation time and the acquisition of a more correct solution.

Random Walk와 Simplex 방법을 이용한 V-shape 매입형 영구자석 동기전동기의 코깅토크 저감 최적 설계

오제민(Je Min Oh),방태경(Tae-Kyoung Bang),신경훈(Kyung-Hun Shin),최장영(Jang-Young Choi),조한욱(Han-Wook Cho) 대한전기학회 2021 전기학회논문지 Vol.70 No.1

This paper presents random walk and simplex optimization algorithm on an optimal design of V-shape interior permanent synchronous motor (V-shape IPMSM). The IPMSM can easily generates a cogging torque because of change in magnetic circuit by interaction between permanent magnets and stator slots. Therefore minimization of the cogging torque, which generates vibration and noise, is an important factor in design of IPMSM. This paper proposes the optimal shape design of V-shape IPMSM using random walk and simplex method for minimizing cogging torque.

오염총량관리를 위한 오염부하량의 최적할당에 관한 연구 (남한강 유역에의 적용)

유병로 ( Byong-ro Ryu ) 한국환경기술학회 2006 한국환경기술학회지 Vol.7 No.1

오염총량관리제가 본격 시행되면서 오염부하량의 할당방법을 놓고 이견이 초래되고 있다. 그동안 각종 법률에 의거 농도에 대하여 할당받은 시설들도 지역의 특성, 배출시설의 종류 및 규모에 따라 다르게 규제농도가 설정되어 있고 신규 시설에 대하여는 더욱 엄격한 진입장벽이 적용되기 때문에 형평성에 문제가 되고 있는 것이다. 그동안 오염부하량 할당은 기득권을 어느정도 인정하면서 일정율 삭감방법을 주로 적용해 왔다. 본 연구에서 제시한 방법은 오염원의 종류, 처리시설 및 방법의 경제성, 목표지점에의 기여도 등을 중심으로 최적화 기법을 적용하여 가장 경제적으로 목표수질을 달성을 할 수 있는 방법을 제시한 것이다. 본 연구방법은 충주댐에서 팔당댐 유입부까지 남한강 본류구간에 유입되는 지천의 오염부하의 최적 할당에 적용하였다. 또 본 연구는 하천의 유입 오염물의 경제적 처리율 결정이나, 신규 오염원의 적정배치 등 오염원 관리를 위해 최적화 기법을 사용하기 위한 시험연구로서 처리장 건설에 소요되는 경비 등 일부자료가 현실과 다를 수 있기 때문에 본 연구의 결과를 그대로 사용할 수는 없다. 최적화 방법으로는 Simplex법의 일종인 Nice LP를 사용하였으며 연구결과 각 유입치천의 오염원 최적 제거율 및 제거비용을 구할 수 있었으며, 이를 토대로 한 최적 할당을 할 수 있었다. The purpose of this study is to propose a method for the optimal allocation of pollutant loads for TMDLs(Total Maximum Daily Loads). To accomplish this purpose, this study is applied the Nice LP(Liner Programming), as one of the Simplex methods. South Han river is selected to test. QUAL2EU simulation model is used to get the velocity and deoxygenation rate data on the stream. The results from the Simplex LP solution give us the removal ratio of wastewater treatment and optimal allocation of waste loads in tributaries. treatment cost and reduces cost data. From the results of calculation by Simplex LP solution, Minimum objective value is 85.29 billion Won.

하이브리드 유전자 알고리즘과 다중목적함수를 적용한 플레이트 거더교의 격자모델에 대한 유한요소 모델개선

정대성,김철영 한국지진공학회 2008 한국지진공학회논문집 Vol.12 No.6

본 논문에서는 거더교 형식을 갖는 교량구조물의 격자 유한요소모델에 대한 모델개선을 위해 하이브리드 유전자 알고리즘에 기초한 유한요소 모델개선기법을 제안하였다. 하이브리드 유전자 알고리즘은 유전자 알고리즘과 심플렉스 최적화방법에 기초한 직접탐색기법으로 구성하였다. 제안된 기법에 적용할 수 있도록 고유진동수, 모드형상 및 정적 처짐에 대한 계측값과 유한요소해석 결과를 사용한 적합함수를 제시하고, 강성과 질량을 동시에 개선할 수 있도록 이들 세 가지 적합함수의 선형 조합 형태를 갖는 다중목적함수를 제시하였다. 제안된 방법은 2경간 연속 격자 유한요소모델의 수치예제와 단경간 플레이트 거더교에 대하여 검증하였다. 수치예제의 경우, 랜덤 노이즈를 고려한 계측오차의 영향을 수치해석적으로 평가하였다. 수치해석과 실험적 검증을 통해, 제안된 방법이 거더교 형식의 교량에 대한 유한요소 모델개선에 적합하고 효과적임을 검증하였다. In this study, a finite element (FE) model updating method based on the hybrid genetic algorithm (HGA) is proposed to improve the grillage FE model for plate girder bridges. HGA consists of a genetic algorithm (GA) and direct search method (DS) based on a modification of Nelder & Mead's simplex optimization method (NMS). Fitness functions based on natural frequencies, mode shapes, and static deflections making use of the measurements and analytical results are also presented to apply in the proposed method. In addition, a multi-objective function has been formulated as a linear combination of fitness functions in order to simultaneously improve both stiffness and mass. The applicability of the proposed method to girder bridge structures has been verified through a numerical example on a two-span continuous grillage FE model, as well as through an experimental test on a simply supported plate girder skew bridge. In addition, the effect of measuring error is considered as random noise, and its effect is investigated by numerical simulation. Through numerical and experimental verification, it has been proven that the proposed method is feasible and effective for FE model updating on plate girder bridges.

Development of integrated evolutionary optimization algorithm and its application to optimum design of ship structures

Young-MO Kong,Su-Hyun Choi,양보석,최병근 대한기계학회 2008 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.22 No.7

This paper proposes an integrated evolutionary optimization algorithm (IEOA) which is combined with genetic algo-rithm (GA), random tabu search method (TS) and response surface methodology (RSM). This algorithm, in order to improve the convergent speed that is thought to be the demerit of GA, uses RSM and the simplex method. Though mutation of GA offers random variety, systematic variety can be secured through the use of tabu-list. Efficiency of this method has been proven by applying traditional test functions and comparing the results to GA. And it is an evidence that the newly suggested algorithm can effectively find the global optimum solution by applying it to minimize the weight of fresh water tank that is placed in the rear of ship designed to avoid resonance. According to the results, GA's convergent speed in initial phase has been improved by using RSM. An optimized solution was calculated without the evaluation of additional actual objective function. Finally, it can be concluded that IEOA is a very useful global optimi-zation algorithm from the viewpoint of co