• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1988년도 가을 학술발표회 논문집
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• pp.55-60
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• 1988

This paper concentrates on the development of simplified and effective algorithm for optimum reinforced concrete(RC) member design. After constructing the data base of predetermined RC sections which are arranged in the order of increasing resistant capacity. Then, the relationship between the section identification numbers and resistant capacities of sections is estabilished by regression and it can be used to obtain the initial solution(section) which satisfies the design constraints imposed. Assuming that there exists the optimum section near the initially selected one, the direct search is conducted to find the discrete optimum solution. The optimization of the entire structure is accomplished through the individual member optimization.

• 한국공간구조학회논문집
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• 제1권1호
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• pp.125-134
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• 2001

The objective of this study is the development of size discrete optimum design algorithm which is based on the GAs(genetic algorithms). The algorithm can perform size discrete optimum designs of space trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses and the constraints are limite state design codes(1998) and displacements. The basic search method for the optimum design is the GAs. The algorithm is known to be very efficient for the discrete optimization. This study solves the problem by introducing the GAs. The GAs consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. In the genetic process of the simple GAs, there are three basic operators: reproduction, cross-over, and mutation operators. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying GAs to optimum design examples.

• Smart Structures and Systems
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• 제14권1호
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• 한국가스학회지
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• 제6권1호
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• pp.86-91
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• 2002

본 연구에서는 장치가 가지고 있는 신뢰도 데이터와 가격을 고려하여 공정에서 요구하는 신뢰도에 도달할 수 있도록 최적화 분석을 수행하여 어떠한 장치를 선택하는가에 대한 방법을 제시하였다. 이산함수를 이용한 목적함수와 제한 조건을 이용하여 보다 실질적인 최적화 문제를 구성하였다. 재? 반응기를 대상으로 하여 시스템에서 요구하는 신뢰도 목표 값에 도달하기 위해 가격에 따라 다른 고장률을 가지는 장치에 대하여 최적화 분석을 수행하였다. 이러한 최적화 분석을 수행하기 위해 mixed-integer programming(MIP) 방법을 사용하였다. 재? 반응기의 신뢰도 목표값이 $1.65{\times}10^{-04}$일 경우에 최적화 분석 수행결과는 가격과 고장률이 모두 좋은 장치로 분석되었다. 그러나 신뢰도 목표값이 낮을 경우 최적화 분석의 수행결과는 비싼 장치의 선택보다 가격과 신뢰도가 낮은 장치를 선택함으로써 원하는 신뢰도 목표값에 도달할 수 있었다.

• 한국기계가공학회지
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• 제21권1호
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• pp.102-110
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• 2022

This paper proposes a solution to the problems of manufacturing cost and processability by applying discrete material and thickness optimization (DMTO) and minimizing the use of high-strength, lightweight materials in the optimization process. A simple infant pop-up seat model was selected as the application target, and the weight reduction effect and variation in strength according to the optimization results were observed. In this study, a simplified finite element model of an infant pop-up seat frame was first constructed. The model was used to perform a static structural analysis to verify the weight and strength of each part. The D-optimal design of the experimental method was then used to observe the influence of each part on the weight and strength. This process was applied using discrete thickness optimization (DTO) (which applies high-strength, lightweight materials and optimizes only the thickness) and DMTO (which considers both the material and thickness). The DTO and DMTO results were compared to verify the design method that determines the major parts and simultaneously considers the material and thickness. Accordingly, in this study, an optimal lightweight design that satisfied the strength standards of the seat frame was derived. Furthermore, discretization parameters were used to minimize the application of high-strength, lightweight materials.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2293-2295
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• 2000

This paper describes the synthesis of robust decentralized controllers for uncertain large-scale discrete-time systems with time-delays in subsystem interconnections. Based on the Lyapunov method, a sufficient condition for robust stability, is derived in terms of a linear matrix inequality(LMI). The solutions of the LMI can be easily obtained using various efficient convex optimization techniques. A numerical example is given to illustrate the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(I)
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• pp.786-790
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• 1987

An optimization problem minimizing n given time-weighted performance index for discrete-time linear multi-input systems is investigated for the prespecified closed-loop eigenvalues. Necessary conditions for an optimality of the controller that satisfies the specified closed-loop eigenvalues are derived. A computational algorithm solving the optimal constant feedback gain is presented and a numerical example is given to show the effect of a time-weighted performance index on the transient responses.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.151-160
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• 2004

Genetic algorithm is the theory of grafting the principle of survival of the fittest in genetics on to the computer algorithm and it is used to solve the optimization problems, especially the shape and size optimization of the structure in Architectural problems. In the size optimization problem discrete variables are used, but series variables have to be used in the shape optimization problem because of the incongruenty. The purpose of this study is to obtain the optimum shape of cable domes by using the real coding genetic algorithm. Generally, the structural performance of the cable domes is influenced very sensitively by pre-stress, geometry and length of the mast because of its flexible characteristic. So, it is very important to decide the optimum shape to get maximum stiffness of cable domes. We use the model to verify the usefulness of this algorithm for shape optimization and analyze the roof system of Seoul Olympic Gymnastic Arena as analytical model of a practical structures. It is confirmed lastly that the optimum shape domes have more stiffness than initial shape ones.

• Journal of Mechanical Science and Technology
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• 제18권9호
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• pp.1512-1518
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• 2004

Rescaled Simulated Annealing (RSA) has been adapted to solve combinatorial optimization problems in which the available computational resources are limited. Simulated Annealing (SA) is one of the most popular combinatorial optimization algorithms because of its convenience of use and because of the good asymptotic results of convergence to optimal solutions. However, SA is too slow to converge in many problems. RSA was introduced by extending the Metropolis procedure in SA. The extension rescales the state's energy candidate for a transition before applying the Metropolis criterion. The rescaling process accelerates convergence to the optimal solutions by reducing transitions from high energy local minima. In this paper, structural optimization examples using RSA are provided. Truss structures of which design variables are discrete or continuous are optimized with stress and displacement constraints. The optimization results by RSA are compared with the results from classical SA. The comparison shows that the numbers of optimization iterations can be effectively reduced using RSA.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.9-14
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• 2003

SGA (Single Genetic Algorithm) is a heuristic global optimization method based on the natural characteristics and uses many populations and stochastic rules. Therefore SGA needs many function evaluations and takes much time for convergence. In order to solve the demerits of SGA, $\mu$GA(Micro-Genetic Algorithm) has recently been developed. In this study, $\mu$GA which have small populations and fast convergence rate, was applied to structural optimization with discrete or integer variables such as 3, 10 and 25 bar trusses. The optimized results of $\mu$GA were compared with those of SGA. Solutions of $\mu$GA for structural optimization were very similar or superior to those of SGA, and faster convergence rate was obtained. From the results of examples, it is found that $\mu$GA is a suitable and very efficient optimization algorithm for structural design.