• 제목/요약/키워드: Function Optimization

검색결과 3,315건 처리시간 0.032초

GENERALIZATIONS OF ISERMANN'S RESULTS IN VECTOR OPTIMIZATION

  • Lee, Gue-Myung
    • 대한수학회보
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    • 제30권1호
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    • pp.1-7
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    • 1993
  • Vector optimization problems consist of two or more objective functions and constraints. Optimization entails obtaining efficient solutions. Geoffrion [3] introduced the definition of the properly efficient solution in order to eliminate efficient solutions causing unbounded trade-offs between objective functions. In 1974, Isermann [7] obtained a necessary and sufficient condition for an efficient solution of a linear vector optimization problem with linear constraints and showed that every efficient solution is a properly efficient solution. Since then, many authors [1, 2, 4, 5, 6] have extended the Isermann's results. In particular, Gulati and Islam [4] derived a necessary and sufficient condition for an efficient solution of a linear vector optimization problem with nonlinear constraints, under certain assumptions. In this paper, we consider the following nonlinear vector optimization problem (NVOP): (Fig.) where for each i, f$_{i}$ is a differentiable function from R$^{n}$ into R and g is a differentiable function from R$^{n}$ into R$^{m}$ .

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Structural damage detection based on MAC flexibility and frequency using moth-flame algorithm

  • Ghannadi, Parsa;Kourehli, Seyed Sina
    • Structural Engineering and Mechanics
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    • 제70권6호
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    • pp.649-659
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    • 2019
  • Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.

크라우드 소싱을 이용한 변환함수 최적화 (Transfer Function Optimization Using Crowd Sourcing)

  • 남진현;남두희
    • 한국인터넷방송통신학회논문지
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    • 제14권4호
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    • pp.107-112
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    • 2014
  • 본 연구에서는 다중 사용자 환경의 볼륨 가시화(Volume Rendering)에서 변환 함수(Transfer Function)의 최적화 방안을 연구한다. 볼륨 데이터에 따라 필요한 변환 함수의 형태가 다르기 때문에 여러 번의 시행착오를 겪어야 필요한 변환 함수를 얻을 수 있는데, 이를 방지하기 위해 크라우드 소싱 기법을 이용하여 변환 함수의 파라미터를 최적화 하는 방안을 제안한다. 다중 사용자 환경에서 각 사용자마다 신뢰도에 따른 레벨을 지정하여 가중치로 사용한다. 이전 사용자가 사용했던 변환 함수 파라미터는 가중치만큼 다음 사용자에게 제공되기 때문에 다음 사용자는 변환 함수의 최적 파라미터를 찾기 위한 시도횟수를 줄일 수 있다.

도로의 최적노선대 선정방법 비교 연구 (Comparative Study on Determining Highway Routes)

  • 김관중;장명순
    • 한국도로학회논문집
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    • 제8권4호
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    • pp.159-179
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    • 2006
  • 도로의 구조 시설기준에 관한 규칙과 국도의 노선계획 설계지침에 준하여 실행되는 현행 노선선정방법과, 컴퓨터 발전과 함께 국내외에서 연구되고 있는 선형최적화 모형식으로 사례연구 구간의 도로 노선을 선정하여 노선 특성을 비교 분석해본 결과, 현행 노선선정방법은 단계별, 구간별로 순차적인 노선선정이 이루어지는 국지적 최적을 추구하나, 선형 최적화 모형식 선정방법은 모든 설계요소가 동시에 고려된 체계최적(System Optimal)의 노선탐색 능력이 있는 것으로 분석되었다. 또한 선형최적화 모형에서 기존 설계공종별 실제공사비로 비용함수를 보정하여 노선을 선정한 결과 현실에 부합되게 설계되었으며, 경제성이 높은(B/C=1.66) 대안 노선이 탐색되었다. 선형최적화 설계모형은 터널 종단에서 종단 경사가 변화하는 등 보완될 점이 있음에도 타당성조사와 기본설계단계에서 노선선정 도구로서 설계시간 및 비용단축, 다양한 대안 노선의 검토 등의 많은 장점을 지니고 있음이 확인되었다.

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A new multi-stage SPSO algorithm for vibration-based structural damage detection

  • Sanjideh, Bahador Adel;Hamzehkolaei, Azadeh Ghadimi;Hosseinzadeh, Ali Zare;Amiri, Gholamreza Ghodrati
    • Structural Engineering and Mechanics
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    • 제84권4호
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    • pp.489-502
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    • 2022
  • This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

Optimal design of reinforced concrete plane frames using artificial neural networks

  • Kao, Chin-Sheng;Yeh, I-Cheng
    • Computers and Concrete
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    • 제14권4호
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    • pp.445-462
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    • 2014
  • To solve structural optimization problems, it is necessary to integrate a structural analysis package and an optimization package. There have been many packages that can be employed to analyze reinforced concrete plane frames. However, because most structural analysis packages suffer from closeness of systems, it is very difficult to integrate them with optimization packages. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrates Design, Analysis, Modeling, Definition, and Optimization phases into an integration environment as follows. (1) Design: first generate many possible structural design alternatives. Each design alternative consists of many design variables X. (2) Analysis: employ the structural analysis software to analyze all structural design alternatives to obtain their internal forces and displacements. They are the response variables Y. (3) Modeling: employ artificial neural networks to build the models Y=f(X) to obtain the relationship functions between the design variables X and the response variables Y. (4) Definition: employ the design variables X and the response variables Y to define the objective function and constraint functions. (5) Optimization: employ the optimization software to solve the optimization problem consisting of the objective function and the constraint functions to produce the optimum design variables. The RC frame optimization problem was examined to evaluate the DAMDO approach, and the empirical results showed that it can be solved by the approach.

인공위성 카메라 주반사경의 위상최적화 (Topology Optimization of the Primary Mirror of a Multi-Spectral Camera)

  • 박강수;장수영;이응식;윤성기
    • 대한기계학회논문집A
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    • 제26권6호
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    • pp.1194-1202
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    • 2002
  • A study on the topology optimization of a multi-spectral camera for space-use is presented. The optimization is carried out under self-weight and polishing pressure loading. A multi-spectral camera for space-use experiences degradation of optical image in the space, which can not be detected on the optical test bench on the earth. An optical surface deformation of a primary mirror, which is a principal component of the camera system, is an important factor affecting the optical performance of the whole camera system. In this study, topology optimization of the primary mirror of the camera is presented. As an objective function, a measure of Strehl ratio is used. Total mass of the primary mirror is given as a constraint to the optimization problem. The sensitivities of the objective function and constraint are calculated by direct differentiation method. Optimization procedure is carried out by an optimality criteria method. For the light-weight primary mirror design, a three dimensional model is treated. As a preliminary example, topology optimization considering a self-weight loading is treated. In the second example, the polishing pressure is also included as a loading in the topology optimization of the mirror. Results of the optimized design topology for the mirror with various mass constraints are presented.

크리깅 근사모델을 이용한 전역적 강건최적설계 (A Global Robust Optimization Using the Kriging Based Approximation Model)

  • 박경진;이권희
    • 대한기계학회논문집A
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    • 제29권9호
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    • pp.1243-1252
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    • 2005
  • A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

적응적 내부 경계를 갖는 레벨셋 방법을 이용한 쉘 구조물의 위상최적설계 (Topology Optimization of Shell Structures Using Adaptive Inner-Front(AIF) Level Set Method)

  • 박강수;윤성기
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2007년도 정기 학술대회 논문집
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    • pp.157-162
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    • 2007
  • A new level set based topology optimization employing inner-front creation algorithm is presented. In the conventional level set based topology optimization, the optimum topology strongly depends on the initial level set distribution due to the incapability of inner-front creation during optimization process. In the present work, in this regard, an inner-front creation algorithm is proposed. in which the sizes. shapes. positions, and number of new inner-fronts during the optimization process can be globally and consistently identified by considering both the value of a given criterion for inner-front creation and the occupied volume (area) of material domain. To facilitate the inner-front creation process, the inner-front creation map which corresponds to the discrete valued criterion of inner-front creation is applied to the level set function. In order to regularize the design domain during the optimization process, the edge smoothing is carried out by solving the edge smoothing partial differential equation (PDE). Updating the level set function during the optimization process, in the present work, the least-squares finite element method (LSFEM) is employed. As demonstrative examples for the flexibility and usefulness of the proposed method. the level set based topology optimization considering lightweight design of 3D shell structure is carried out.

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균질화법을 이용한 수직형 롤러 분쇄기용 테이블 라이너의 위상최적설계에 관한 연구 (A Study on Topology Optimization of Table Liner for Vertical Roller Mill using Homogenization Method)

  • 이동우;홍순혁;조석수;이선봉;주원식
    • 한국정밀공학회지
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    • 제20권6호
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    • pp.113-122
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    • 2003
  • Topology optimization is begun with layout optimization that is attributed to Rozvany and Prager of the 1960's. They claimed that structure was transformed into truss connecting all the nodes of finite element and optimized by control of its sectional modulus. But, this method is partial topology optimization. General layout optimal design appliable to continum structure was proposed by Bendsoe and Kikuchi in 1988. Topology optimization expresses material stiffness of structure into function of arbitrary variable. If this variable is 1, material exists but if this variable is 0, material doesn't exist. Therefore, topology optimization searches the distribution function of material stiffness for structure. There are a few researchs for simple engineering problem such as topology optimization of square plane structure or truss structure. So, This study applied to topology optimization of table liner for vertical roller mill that is the largest scale in the world. After table liner decreased by 20% of original weight, the structure analysis for first optimized model was performed.