• 대한기계학회논문집A
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• 제25권3호
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• pp.369-380
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• 2001

Although extensive efforts have been devoted to the optimal design of composite laminated plates in recent years, some practical issues still need further research. Two of them are: the handling of the ply angle as either continuous or discrete; and that of the uncertainties in material properties, which were treated as continuous and ignored respectively in most researches in the past. In this paper, an algorithm for stacking sequence optimization which deals with discrete ply angles and that for thickness optimization which considers uncertainties in material properties are used for a two step optimization of composite laminated plates. In the stacking sequence optimization, the branch and bound method is modified to handle discrete variables; and in the thickness optimization, the convex modeling is used in calculating the failure criterion, given as constraint, to consider the uncertain material properties. Numerical results show that the optimal stacking sequence is found with fewer evaluations of objective function than expected with the size of feasible region taken into consideration; and the optimal thickness increases when the uncertainties of elastic moduli considered, which shows such uncertainties should not be ignored for safe and reliable designs.

• 한국전산구조공학회논문집
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• 제16권3호
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• pp.237-250
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• 2003

강바닥판교는 수 천개의 부재가 연결된 복잡한 구조물이기 때문에 설계와 해석이 난해하다는 단점을 가지고 있어 구조특성에 적합한 효율적인 최적화 알고리즘을 개발하는 것은 실용적인 최적화이론의 활용차원에서 매우 중요하다고 할 수 있다. 이에 본 연구에서는 강바닥판교의 최적설RP를 효과적으로 수행하기 위한 개선된 다단계 최적설계 알고리즘을 제안하였다. 강바닥판교의 구조적인 특성을 반영하면서 전체 시스템을 주형과 강바닥판으로 나누기 위해 다단계 최적설계 방법 중에 하나인 등위법 (Coordination Method)을 사용하였고, 효율적인 최적설계를 위한 처짐제약조건 소거기법, 구조해석의 효율성을 높이기 위한 자동미분기법이 사용되었으며, 활하중에 의한 응력은 기존연구에서 제안된 응력재해석 기법을 사용하였다. 강바닥판은 폐단면리브의 형식과 같은 이산형 설계변수와 바닥판의 두께 가로보의 치수와 같은 연속형 설계변수가 혼합되어 있는 형태로 구성되어 있다. 이에 본 연구에서는 강 바닥판의 최적화를 위해 수정된 유전자 알고리즘을 사용하였다. 수치예제를 사용하여 제안된 알고리즘의 효율성과 수렴성을 입증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4355-4371
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• 2020

Phase retrieval, recovering a signal from phaseless measurements, is generally considered to be an NP-hard problem. This paper adopts an amplitude-based nonconvex optimization cost function to develop a new stochastic gradient algorithm, named stochastic reweighted phase retrieval (SRPR). SRPR is a stochastic gradient iteration algorithm, which runs in two stages: First, we use a truncated sample stochastic variance reduction algorithm to initialize the objective function. The second stage is the gradient refinement stage, which uses continuous updating of the amplitude-based stochastic weighted gradient algorithm to improve the initial estimate. Because of the stochastic method, each iteration of the two stages of SRPR involves only one equation. Therefore, SRPR is simple, scalable, and fast. Compared with the state-of-the-art phase retrieval algorithm, simulation results show that SRPR has a faster convergence speed and fewer magnitude-only measurements required to reconstruct the signal, under the real- or complex- cases.

• 대한기계학회논문집A
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• 제25권10호
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• pp.1621-1626
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• 2001

The structural optimization have been carried out in the continuous design space or in the discrete design space. Methods fur discrete variables such as genetic algorithms , are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete des inn space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions leer constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 춘계학술대회 논문집
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• pp.118-123
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• 2004

In this study, genetic algorithm mixed binary and real encoding is proposed to deal with design variables of various types. And that is applied to optimum design of Multi-stage gear drive. Design of pressure vessel which is mixed discrete and continuous variables is applied to verify reasonableness of proposed genetic algorithm. The proposed genetic algorithm is applied for the gear ratio optimization and the volume minimization of geared motor which is used in field. In result, it shows that the volume has decreased about 8% compared with the existing geared motor.

• Journal of Computing Science and Engineering
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• 제3권1호
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• pp.27-58
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• 2009

Aggregation join queries are an important class of queries over data streams. These queries involve both join and aggregation operations, with window-based joins followed by an aggregation on the join output. All existing research address join query optimization and aggregation query optimization as separate problems. We observe that, by putting them within the same scope of query optimization, more efficient query execution plans are possible through more versatile query transformations. The enabling idea is to perform aggregation before join so that the join execution time may be reduced. There has been some research done on such query transformations in relational databases, but none has been done in data streams. Doing it in data streams brings new challenges due to the incremental and continuous arrival of tuples. These challenges are addressed in this paper. Specifically, we first present a query processing model geared to facilitate query transformations and propose a query transformation rule specialized to work with streams. The rule is simple and yet covers all possible cases of transformation. Then we present a generic query processing algorithm that works with all alternative query execution plans possible with the transformation, and develop the cost formulas of the query execution plans. Based on the processing algorithm, we validate the rule theoretically by proving the equivalence of query execution plans. Finally, through extensive experiments, we validate the cost formulas and study the performances of alternative query execution plans.

• 전산구조공학
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• 제8권2호
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• pp.123-132
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• 1995

Genetic Algorithms(GA)는 생명체의 자연진화 법칙에 기초한 최적화 방법으로 그 범용성이 높이 평가되어지고 있다. 기존의 GA는 대부분 설계변수로 2진수형 코드를 사용하는데, 이는 실수형 설계변수로 구성된 최적화 문제를 해결하기 위해 컴퓨터 주 기억용량을 많이 사용하여야 하며, 계산 시간 면에서도 비효율적이고 또한 국부탐색 능력도 떨어지는 단점이 있다. 따라서 본 연구에서는 GA에 의한 최적화과정에서 실수형 설계변수를 직접 사용할 수 있도록 교배와 돌연변이 과정을 새로이 정식화하였다. 그리고 여러 형태의 단일 및 다목적함수 최적화 문제에 대해 실수형 GA와 2진수형 GA의 결과를 비교 검토하였다. 비교 검토 결과, 실수형 GA의 성능이 2진수형 GA보다 우수함을 알 수 있었고, 일반 최적화 방법으로 실수형 GA를 사용하여도 무방하리라 본다.

• 소음진동
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• 제8권4호
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• pp.632-642
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• 1998

A method based on finite element discretization is developed for optimizing the polarization profile of PVDF film to create the modal transducer for specific modes. Using this concept, one can design the modal transducer in two-dimensional structure having arbitrary geometry and boundary conditions. As a practical means for implementing this polarization profile without repoling the PVDF film the polarization profile is approximated by optimizing electrode patterns, lamination angles, and poling directions of the multi-layered PVDF transducer. This corresponds to the approximation of a continuous function using discrete values. The electrode pattern of each PVDF layer is optimized by deciding the electrode of each finite element to be used or not. Genetic algorithm, suitable for discrete problems, is used as an optimization scheme. For the optimization of each layers lamination angle, the continuous lamination angle is encoded into discrete value using binary 5 bit string. For the experimental demonstration, a modal sensor for first and second modes of cantilevered composite plate is designed using two layers of PVDF films. The actuator is designed based on the criterion of minimizing the system energy in the control modes under a given initial condition. Experimental results show that the signals from residual modes are successfully reduced using the optimized multi-layered PVDF sensor. Using discrete LQG control law, the modal peaks of first and second modes are reduced in the amount of 12 dB and 4 dB, resepctively.

• Structural Engineering and Mechanics
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• 제85권3호
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• pp.369-379
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• 2023

Reliability-Based Design Optimization (RBDO) is an appropriate framework for obtaining optimal designs by taking uncertainties into account. Large-scale problems with implicit limit state functions and problems with discrete design variables are two significant challenges to traditional RBDO methods. To overcome these challenges, this paper proposes a hybrid method to perform RBDO of structures that links Firefly Algorithm (FA) as an optimization tool to advanced (finite element) reliability methods. Furthermore, the Genetic Algorithm (GA) and the FA are compared based on the design cost (objective function) they achieve. In the proposed method, Weighted Simulation Method (WSM) is utilized to assess reliability constraints in the RBDO problems with explicit limit state functions. WSM is selected to reduce computational costs. To performing RBDO of structures with finite element modeling and implicit limit state functions, a First-Order Reliability Method (FORM) based on the Direct Differentiation Method (DDM) is utilized. Four numerical examples are considered to assess the effectiveness of the proposed method. The findings illustrate that the proposed RBDO method is applicable and efficient for RBDO problems with discrete and continuous design variables and finite element modeling.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.559-560
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• 2021

차등 진화는 연속 최적화 문제를 해결하기 위한 효율적인 알고리즘이다. 그러나 대규모 최적화 문제를 해결하기 위해 차등 진화를 적용하면 성능이 급격히 저하되고 런타임이 기하급수적으로 증가한다. 따라서 Spark(SparkDECC로 알려짐)를 기반으로 하는 새로운 협력 공진화 차동 진화가 제안된다. 분할 정복 전략은 SparkDECC에서 사용된다.