• Title/Summary/Keyword: Functional optimization

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ON AUGMENTED LAGRANGIAN METHODS OF MULTIPLIERS AND ALTERNATING DIRECTION METHODS OF MULTIPLIERS FOR MATRIX OPTIMIZATION PROBLEMS

  • Gue Myung, Lee;Jae Hyoung, Lee
    • Nonlinear Functional Analysis and Applications
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    • v.27 no.4
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    • pp.869-879
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    • 2022
  • In this paper, we consider matrix optimization problems. We investigate augmented Lagrangian methods of multipliers and alternating direction methods of multipliers for the problems. Following the proofs of Eckstein [3], and Eckstein and Yao [5], we prove convergence theorems for augmented Lagrangian methods of multipliers and alternating direction methods of multipliers for the problems.

A New Algorithm for Optimal Real and Reactive Power Dispatch (최적유효 및 무요전력배분을 위한 신 앨고리즘)

  • Park, Young-Moon;Lee, Kwang-Yon
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.32 no.4
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    • pp.145-154
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    • 1983
  • This paper presents a new method for optimal real and reactive power dispatch for the economic operation of a power system. Unlike the usual approach of minimizing the transmission loss, this method minimizes the total production cost not only for the real power optimization problem, but also for the reactive power optimization. The control variables are real power generation of units for real power optimization, and reactive power optimization. The constraints are the operating limits on these control variables and the limits on the bus voltages. Methematical models are developed to represent the sensitivity relationships between dependent and control variables for both real and reactive power optimization modules, and thus eliminate the use of B-coefficients. In order to handle many functional inequality constraints, a modified version of the gradient projection method is developed for optimization procedure, and has shown a remarkable advantage in computation efficiency.

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Topology Design Optimization of a Magnetic System Consisting of Permanent Magnets and Yokes and its Application to the Bias Magnet System of a Magnetostrictive Sensor (영구자석과 요크를 포함한 자기 시스템의 위상최적설계 및 자기 변형 센서의 바이어스 자석 설계에의 응용)

  • Cho, Seung-Hyun;Kim, Yoon-Young;Yoo, Jeong-Hoon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.11
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    • pp.1703-1710
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    • 2004
  • The objective of this investigation is to formulate and carry out the topology optimization of a magnetic system consisting of permanent magnets and yokes. Earlier investigations on magnetic field topology optimization have been limited on the design optimization of yokes or permanent magnets alone. After giving the motivation for the simultaneous design of permanent magnets and yokes, we develop the topology optimization formulation of the coupled system by extending the technique used in structural problems. In the present development, we will also examine the effects of the functional form for permeability penalization on the optimized topology.

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

  • Park Gyung-Jin;Lee Kwon-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.9 s.240
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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.

Optimization Method for a Coupled Design, Considering Robustness (강건성을 고려한 연성설계의 최적화 방법)

  • Kang, Dong-Heon;Song, Byoung-Cheol;Park, Young-Chul;Lee, Kwon-Hee
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.7 no.2
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    • pp.8-15
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    • 2008
  • Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The 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, Taguchi method, reliability-based optimization and robust optimization are being used. Based on the independence axiom of axiomatic design theory that illustrates the relationship between desired specifications and design parameters, the designs can be classified into three types: uncoupled, decoupled and coupled. To best approach the target performance with the maximum robustness is one of the main functional requirements of a mechanical system. Most engineering designs are pertaining to either coupled or decoupled ones, but these designs cannot currently accomplish a real robustness thus a trade-off between performance and robustness has to be made. In this research, the game theory will be applied to optimize the trade-off.

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Study for Development of the Fabrication System of Brain Model for Surgery Emulation (모의수술용 뇌모형 제작시스템 개발을 위한 연구)

  • 염상원;방재철;엄태준;주영철;김승우;공용해;천인국;김범태
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.298-298
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    • 2000
  • This paper presents the optimization technique to analyze the effect of the design parameters of rapid prototyping system for human brain model fabrication. The optimization method considers the functional relationships among the design parameters such as thickness gap, shrink rate, and laser speed that govern the operation of fabrication system. This paper applies a discrete optimization technique as the optimization method to determine the dominant parameter values. Additional study includes manner of complement surface image of ellipse which approximates the brain model using the adaptive slicing and the offset contour. According to the parameters tuning and interaction of effect, more suitable parameter values can be obtained by enhanced 3D brain model fabrication.

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A direct treatment of Min-Max dynamic response optimization problems (Min-Max형 동적 반응 최적화 문제의 직접 처리기법)

  • 박흥수;김종관;최동훈
    • Journal of the korean Society of Automotive Engineers
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    • v.15 no.1
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    • pp.81-88
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    • 1993
  • A direct treatment of the min-max type objective function of the dynamic response optimization problem is proposed. Previously, the min-max type objective function was transformed to an artificial design variable and an additional point-wise state variable constraint function was imposed, which increased the complexity of the optimization problem. Especially, the design sensitivity analysis for the augmented Lagrangian functional with the suggested treatment is established by using the adjoint variable method and a computer program to implement the proposed algorithm is developed. The optimization result of the proposed treatment are obtained for three typical problems and compared with those of the previous treatment. It is concluded that the suggested treatment in much more efficient in the computational effort than the previous treatment with giving the similar optimal solutions.

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Identifying Responsive Functional Modules from Protein-Protein Interaction Network

  • Wu, Zikai;Zhao, Xingming;Chen, Luonan
    • Molecules and Cells
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    • v.27 no.3
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    • pp.271-277
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    • 2009
  • Proteins interact with each other within a cell, and those interactions give rise to the biological function and dynamical behavior of cellular systems. Generally, the protein interactions are temporal, spatial, or condition dependent in a specific cell, where only a small part of interactions usually take place under certain conditions. Recently, although a large amount of protein interaction data have been collected by high-throughput technologies, the interactions are recorded or summarized under various or different conditions and therefore cannot be directly used to identify signaling pathways or active networks, which are believed to work in specific cells under specific conditions. However, protein interactions activated under specific conditions may give hints to the biological process underlying corresponding phenotypes. In particular, responsive functional modules consist of protein interactions activated under specific conditions can provide insight into the mechanism underlying biological systems, e.g. protein interaction subnetworks found for certain diseases rather than normal conditions may help to discover potential biomarkers. From computational viewpoint, identifying responsive functional modules can be formulated as an optimization problem. Therefore, efficient computational methods for extracting responsive functional modules are strongly demanded due to the NP-hard nature of such a combinatorial problem. In this review, we first report recent advances in development of computational methods for extracting responsive functional modules or active pathways from protein interaction network and microarray data. Then from computational aspect, we discuss remaining obstacles and perspectives for this attractive and challenging topic in the area of systems biology.

Optimization of Mulberry Jelly Making by Response Surface Methodology

  • Kim, Bo-Ram;Joo, Na-Mi
    • Food Quality and Culture
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    • v.2 no.1
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    • pp.13-19
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    • 2008
  • Recently, though mulberry's superiority as a functional food has been proven, its use as a food material is limited. Therefore, in this study, to develop jelly using mulberry that is compatible with Korean tastes as health functional food by grafting the method to manufacture jelly consumed as a dessert or a snack in the west, according to the central composite design, mulberry jelly was produced by varying the content of citric acid ($X_1$), sucrose ($X_2$), and gelatin ($X_3$) at 5 levels. And by applying the response surface methodology, rheology and sensory preference experiment results were analyzed, the optimization of mulberry jelly manufacturing condition was carried out, and studies on the analysis of composition were performed. As the sensory preference of mulberry jelly, except the flavor, the remaining hardness, elasticity, sweetness, color, and the overall quality were found to be significant. And similarly, it was found to be influenced greatly by gelatin content generally. Based on the overlapped part of categories, in the range of factors that satisfy all the sensory categories, the value located in the middle was calculated, the optimization point was obtained, and it was found to be 6.2 g citric acid, 141.0 g sugar, and 13.5 g gelatin.

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