• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.464-469
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• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.

• Journal of Biosystems Engineering
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• v.11 no.1
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• pp.64-75
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• 1986

The objective of this study was to develop a mathematical model for optimum design of diversified farming systems which have the regional characteristics. For this purpose, the farming surveys were conducted for mainly 1984 agriculture. They were carried out on January and July 1985 for three villages of central region of Korea. The surveyed data were analyzed by systems analysis and the diversified farming systems were modeled. They consist of four and six croping patterns for paddy and upland, two and three kinds of fruit crop and livestock, and seven kinds of farm machinery for each work system. Then a mathematical model was developed by the multiple objective decision making (MODM) method in order to design optimum systems of diversified farming. It consists of 23 decision variables, two objective functions and nine constraint functions. The goals of objective function are maximization of agricultural incomes and power inputs of farm machinery, and the modeled factors for constraint function are arable land, available capital, labor, and land utilization.

• Journal of Ocean Engineering and Technology
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• v.26 no.6
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• pp.80-85
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• 2012

The methods of robust design optimization (RDO) and reliability-based robust design optimization (RBRDO) were implemented in the present study. RBRDO is an integrated method that accounts for the design robustness of an objective function and for the reliability of constraints. The objective function in RBRDO is expressed in terms of the mean and standard deviation of an original objective function. Thus, a multi-objective formulation is employed. The regressive approximate models are generated via the moving least squares method (MLSM) and constraint-feasible moving least squares method (CF-MLSM), which make it possible to realize the feasibility regardless of the multimodality/nonlinearity of the constraint function during the approximate optimization processes. The regression model based RBRDO is newly devised and its numerical characteristics are explored using the design of an actively controlled ten bar truss structure.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.699-704
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• 2000

The present paper deals with a multiobjective optimization method based on the co-evolutionary genetic strategy. The co-evolutionary strategy carries out the multiobjective optimization in such way that it optimizes individual objective function as compared with each generation's value while there are more than two genetic evolutions at the same time. In this study, the designs that are out of the given constraint map compared with other objective function value are excepted by the penalty. The proposed multiobjective genetic algorithms are distinguished from other optimization methods because it seeks for the optimized value through the simultaneous search without the help of the single-objective values which have to be obtained in advance of the multiobjective designs. The proposed strategy easily applied to well-developed genetic algorithms since it doesn't need any further formulation for the multiobjective optimization. The paper describes the co-evolutionary strategy and compares design results on the simple structural optimization problem.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.379-390
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• 2005

In this paper, optimality conditions for multiobjective programming problems having F-convex objective and constraint functions are considered. An equivalent multiobjective programming problem is constructed by a modification of the objective function. Furthermore, an F-Lagrange function is introduced for a constructed multiobjective programming problem, and a new type of saddle point is introduced. Some results for the new type of a saddle point are given.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.220-223
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• 2003

This paper presents VSCOPF(Votage Stability Constrained Optimal Power Flow) algorithm based on SLP(Successive Linear Programming) to interpret the large scale system. Voltage stability index used to this paper is L index to be presented by function form. The objective function consists of load shedding cost minimization. Voltage stability indicator constraint was incorporated in traditional OPF formulation. as well as the objective function and constraints are linearlized and the optimal problem is performed by SLP(Successive Linear Programming). In this paper, the effect of voltage stability limit constraint is showed in the optimal load curtailment problems. As a result, an optimal solution is calculated to minimize load shedding cost guaranteeing voltage security level. Numerical examples using IEEE 39-bus system is also presented to illustrate the capabilities of the proposed formulation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.3
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• pp.275-283
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• 2012

This paper presents a design method of a robust tracking controller satisfying multiple constraints using genetic algorithm. A robust $H_{\infty}$ constraint with loop shaping is used to address disturbance attenuation with error limits and a loop gain constraint is considered so as not to enlarge the tracking loop gain and bandwidth unnecessarily. The robust $H_{\infty}$ constraint is expressed by a matrix inequality and the loop gain constraint is considered as an objective function so that genetic algorithm can be applied. Finally, a robust tracking controller can be obtained by integrating genetic algorithm with LMI approach. The proposed tracking controller design method is applied to the track-following system of an optical DVD recording drive and is evaluated through the experimental results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.49-56
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• 2013

In this paper, for constrained optimization problem, one multi-objective optimization algorithm that ensures both performance robustness and constraint feasibility is proposed when uncertainties are involved in design variables. In the proposed algorithm, the gradient index of objective function assisted by design sensitivity with the help of finite element method is applied to evaluate robustness; the reliability calculated by the sensitivity-assisted Monte Carlo simulation method is used to assess the feasibility of constraint function. As a demonstration, the performance and numerical efficiency of the proposed method is investigated through application to the optimal design of TEAM problem 22--a superconducting magnetic energy storage system.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.920-925
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• 2001

A study on the topology optimization of a multi-spectral camera for space-use is presented. 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, under the self-weight loading 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. 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 criterion method using the sensitivities of the objective function and the constraint. As a preliminary example, topology optimization considering a self-weight loading is treated. For practical use, the polishing pressure is included as a loading in the topology optimization of the primary mirror. Results of the optimized design topology for the primary mirror with varying mass ratios are presented.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.186-191
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• 2015

Presently, rapidly changing and unstable global economic environments demand engineers. Products should be designed to increase profits by lowering costs and provide distinguished performance compared with competitors. This study aims to optimize the design of the power-transmission drive shaft. The mass is reduced as an objective function, and the stress is constrained under a constant value. To reduce the number of experiments, CCD (central composite design) and D-Optimal are used for the experimental design. RSM (response surface methodology) is employed to construct a regression model for the objective functions and constraint function. In this problem, there is only one objective function for the mass. The other objective function gives 1; thus, NSGA-II is used.