• 대한기계학회논문집
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• 제19권2호
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• pp.433-442
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• 1995

For the line search of a multi-variable optimization, an efficient algorithm is presented. The algorithm sequentially employs several polynomial approximations such as 2-point quadratic interpolation, 3-point cubic interpolation/extrapolation and 4-point cubic interpolation/extrapolation. The order of polynomial function is automatically increased for improving the accuracy of approximation. The method of approximation (interpolation or extrapolation) is automatically switched by checking the slope information of the sample points. Also, for selecting the initial step length along the descent vector, a new approach is presented. The performance of the proposed method is examined by solving typical test problems such as mathematical problems, mechanical design problems and dynamic response problems.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1998년도 춘계학술발표회논문집(2)
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• pp.577-582
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• 1998

In nuclear power plant, it has been the important object to reduce the occupational radiation exposure (ORE). Recently, the optimization concept of management science has been studied to reduce the ORE in nuclear power plant. In optimization of the worker allocation, the collective dose, working time, individual dose, an total number of worker must be considered and their priority orders must be thought because the main constraint is necessary for determining the constraints variable of the radiological worker allocation problem. The ultimate object of this study s to look into the change of the optimal allocation of the radiological worker as priority order changes. In this study, the priority order is the characteristic of goal programming that is a kind of multi-objective linear programming. From a result of study using goal programming, the total number of worker and collective dose of worker have changed as the priority order has changed and the collective dose limit have played an important role in reducing the ORE.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 춘계학술대회논문집
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• pp.148-151
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• 2008

In a double-passage cascade apparatus, only two blades are installed in order to increase the accuracy of experimental result by applying bigger blade than the size of multi-blades on the same apparatus. However, this causes difficulties to make correct periodic condition. In this study, sidewalls are designed to meet periodic condition without removing the operating fluid or adjusting tail boards. Surface Mach number on the blade surface is applied to a responsible variable, and 12 design variables which are related with sidewall profile control are selected. A gradient based optimization is adopted for wall design and CFX-11 is used for the internal flow computation. The computed result shows that it could obtain the same flow structure by modifying only the sidewalls of the double-passage cascade apparatus.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.565-581
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• 2019

This paper investigates the wireless powered two way relay network (WPTWRN), where two single-antenna users and one single-antenna relay firstly harvest energy from signals emitted by a multi-antenna power beacon (PB) and then two users exchange information with the help of the relay by using their harvested energies. In order to improve the energy transfer efficiency, energy beamforming at the PB is deployed. For such a network, to explore the performance limit of the presented WPTWRN, an optimization problem is formulated to obtain the achievable rate region bounds by jointly optimizing the time allocation and energy beamforming design. As the optimization problem is non-convex, it is first transformed to be a convex problem by using variable substitutions and semidefinite relaxation (SDR) and then solve it efficiently. It is proved that the proposed method achieves the global optimum. Simulation results show that the achievable rate region of the presented WPTWRN architecture outperforms that of wireless powered one way relay network architecture. Results also show that the relay location has significant impact on achievable rate region of the WPTWRN.

• 한국정밀공학회지
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• 제13권7호
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• pp.66-77
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• 1996

Optimal topology design is to search the optimal configuration of a structure which can be used as a shape at the conceptual design stage. Our objective is to maximize the stiffness of the structures and ribs under a material usage constraintl. The density of each finite element is the design variable and its relationship with Young's modulus is expressed by quadratic form. The configuration is represented by the entire density distribution, the structural analysis is performed by finite element method and the optimiza- tion is performed by Feasible Direction Method. Feasible Direction Method can handle various problems simultaneously, that is, mult-objectives and multi-constraints. Total computation time can be reduced by the quadratic relationship between the density and the material property and fewer design variables than Homogenization Method. Toplogy optimization technique developed in this research is applied to design the shapes of the ribs.

• 한국시뮬레이션학회논문지
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• 제18권4호
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• pp.137-148
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• 2009

본 논문의 목적은 신뢰성 있는 선형회귀모델을 구축하기 위하여 후보독립변수 중 유효변수를 선택하는 알고리즘을 구현하는 것이다. 선형회귀모델을 구축하는데 있어서 데이터 상의 모든 후보독립변수를 포함하는 것은 모델의 통계적 유의성을 감소시킬 수 있으며, 차원의 저주(Curse of dimensionality)를 유발할 수 있고, 데이터의 개수보다 변수의 개수가 많을 경우 모델의 구축이 불가능한 문제점 등이 있다. 이와 같은 문제점을 해결하기 위하여 변수선택의 문제를 조합최적화의 문제로 보고 유전 알고리즘(Genetic Algorithm)을 활용하였다. 일반적으로 선형회귀모델의 통계적 유의성을 평가하는 대표적인 통계량으로는 종속변수에 대한 독립변수의 설명력을 나타내는 결정계수($R^2$), 회귀식의 통계적 유의성을 검정하는 F통계량, 회귀계수의 통계적 유의성을 검정하는 t통계량, 잔차의 표준오차 등이 있다. 모델의 통계적 유의성은 하나의 통계량으로 표현될 수 없으므로 다양한 기준을 고려한 다중목적식(Multi-objective function)을 가지는 유전 알고리즘을 설계하였다. 설계한 알고리즘의 성능평가를 위하여 다양한 조건을 가정한 시뮬레이션 데이터에 적용하였다. 그 결과 구축한 알고리즘이 유효변수를 판단함에 있어 기존의 대표적인 변수선택 알고리즘인 LARS(Least Angle Regression)에 비해 우수한 성능을 보임을 확인할 수 있었다. 또한, 주가 데이터를 이용한 포트폴리오 선택에 적용해 본 결과 우수한 응용문제 해결 능력이 있음을 확인할 수 있었다.

• 산업경영시스템학회지
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• 제31권3호
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• pp.17-23
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• 2008

In this research article, scheduling a casting sequence in a job-shop type foundry involving a variety of casts made of an identical alloy but with different shapes and II weights, has been investigated. The objective is to produce the assigned mixed orders satisfying due dates and obtaining the highest ingot efficiency simultaneously. Implementing simple integer programming instead of complicated genetic algorithms accompanying rigorous calculations proves that it can provide a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Enhancing the ingot efficiency under the constraint of discrete ingot sizes is accomplished by using a simple and intelligible algorithm in a standard integer programming. Employing this simple methodology, a job-shop type foundry is able to maximize the furnace utilization and minimize ingot waste.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.651-652
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• 2008

This research presents a multi-objective optimal design employing topological approach to maximize magnetic energy while minimizing structural deformation which is caused by magnetic reluctance force and magnetostriction. A design sensitivity formula is derived by employing the adjoint variable method (AVM) to avoid numerous sensitivity evaluations for a coupled magneto-mechanical analysis. The sensitivity analysis is verified using the finite difference method (FDM) in a C-shape actuator. A linear actuator used in a home appliance is examined for optimal design and demonstrates the strength of the proposed topology optimization approach.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 C
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• pp.1589-1590
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• 2006

A method to determine functional relationships between the variable physical dimensions of an antenna and the antenna performance characteristics is presented. By applying multi-expression programming (MEP) to this data set, optimization with regard to a given criteria can be subsequently performed on the functions instead of performing repealed electromagnetic simulations. The functionals are trained on an initial population of simulation samples and refined using a point-wise error estimate to identify design parameters for subsequent samples. Additionally, the depth of the MEP tree is adjusted for increased accuracy as the data set is deemed sufficient.

• 지식경영연구
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• 제21권1호
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• pp.27-40
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• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).