• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(C)
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• pp.328-333
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• 2010

최적해를 구하는 효과적인 방법 중 하나인 GA (Genetic Algorithm)은 높은 품질의 해를 구하기 위해서 많은 연산시간이 필요하지만, GPU (Graphics Processing Unit)의 높은 데이터 병렬처리 능력과 우수한 부동소수 연산능력을 이용하면 빠르게 처리 가능하다. 이 논문에서는 GPU를 이용하여 가속한 섬 기반의 RVGA (Real-Valued Genetic Algorithm)와 GPU를 이용하지 않는 RVGA를 비교하여 평가하였으며, 또한 GPU를 이용하지만 RVGA가 아닌 Simple GA인 경우와도 비교하여 평가 하였다. 그 결과, GPU를 이용한 경우 속도 향상을 할 수 있었으며, Simple GA보다 RVGA가 더 속도가 향상되었다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권2호
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• pp.115-121
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• 2002

This paper presents an evolutionary design of digital IIR filters using the genetic algorithm (GA) with modified genetic operators and real-valued encoding. Conventional digital IIR filter design methods involve algebraic transformations of the transfer function of an analog low-pass filter (LPF) that satisfies prescribed filter specifications. Other types of frequency-selective digital fillers as high-pass (HPF), band-pass (BPF), and band-stop (BSF) filters are obtained by appropriate transformations of a prototype low-pass filter. In the GA-based digital IIR filter design scheme, filter coefficients are represented as a set of real-valued genes in a chromosome. Each chromosome represents the structure and weights of an individual filter. GA directly finds the coefficients of the desired filter transfer function through genetic search fur given filter specifications of minimum filter order. Crossover and mutation operators are selected to ensure the stability of resulting IIR filters. Other types of filters can be found independently from the filter specifications, not from algebraic transformations.

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.35-43
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• 2008

The control of underactuated mechanical system is very complex for the loss of its control inputs. The model of underactuated mechanical systems in a potential field is built with Lagrangian method and its structural properties are analyzed in detail. A genetic algorithm (GA)based stable control approach is proposed for the class of under actuated mechanical systems. The Lyapunov stability theory and system properties are utilized to guarantee the system stability to its equilibrium. The real-valued GA is used to adjust the controller parameters to improve the system performance. This approach is applied to the underactuated double-pendulum-type overhead crane and the simulation results illustrate the complex system dynamics and the validity of the proposed control algorithm.

• Computers and Concrete
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• 제11권6호
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• pp.541-569
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• 2013

There is a wide variety of existing Genetic Algorithms (GA) operators and parameters in the literature. However, there is no unique technique that shows the best performance for different classes of optimization problems. Hence, the evaluation of these operators and parameters, which influence the effectiveness of the search process, must be carried out on a problem basis. This paper presents a comparison for the influence of GA operators and parameters on the performance of the damage identification problem using the finite element model updating method (FEMU). The damage is defined as reduction in bending rigidity of the finite elements of a reinforced concrete beam. A certain damage scenario is adopted and identified using different GA operators by minimizing the differences between experimental and analytical modal parameters. In this study, different selection, crossover and mutation operators are compared with each other based on the reliability, accuracy and efficiency criteria. The exploration and exploitation capabilities of different operators are evaluated. Also a comparison is carried out for the parallel and sequential GAs with different population sizes and the effect of the multiple use of some crossover operators is investigated. The results show that the roulettewheel selection technique together with real valued encoding gives the best results. It is also apparent that the Non-uniform Mutation as well as Parent Centric Normal Crossover can be confidently used in the damage identification problem. Nevertheless the parallel GAs increases both computation speed and the efficiency of the method.

• 한국강구조학회 논문집
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• 제23권5호
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• pp.581-593
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• 2011

스티프너로 보강된 플레이트 거더 대신에 주름 웨브를 사용하는 근본적인 장점은 얇은 판으로 형성된 편평한 웨브에서 발생하는 좌굴에 관한 불안정 문제를 해결할 수 있는 것 뿐 아니라 수직 스티프너의 필요성도 함께 해결 됨으로써 경제적인 장점을 제공받게 된다. 따라서 본 연구에서는 사인형 주름 웨브를 가진 보의 구조설계 기법과 실변수 알고리즘을 이용하여 최적화 문제를 다루도록 한다. 구조설계과정과 설계변수들은 EN 1993-1-5, DASt-R015 및 Pasternak 등(2004)을 통해서 구성하며, 주름 웨브의 전단좌굴에 대한 유효한 설계가능영역에 대해 비교, 고찰한다. 구조설계 최적화를 위해서, 목적함수는 사인형 주름 웨브 보의 중량으로 정의하여 최소중량최적화를 수행하며, 제약조건으로는 세장비, 부재력 저항능력 및 보의 허용처짐에 대해서 고려한다. 최종적으로 등분포 하중의 단순보 모델을 해석 대상으로 채택하며, 유전자 연산에 있어서 효율적인 확률변수에 대해 연구한다.

• 대한전기학회논문지:전력기술부문A
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• 제55권9호
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• pp.365-375
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• 2006

This paper is presented by the application of parallel adaptive evolutionary algorithm(PAEA) to search an optimal solution of a thermal unit commitment problem. The adaptive evolutionary algorithm(AEA) takes the merits of both a genetic algorithm(GA) and an evolution strategy(ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. To reduce the execution time of AEA, the developed algorithm is implemented on an parallel computer which is composed of 16 processors. To handle the constraints efficiently and to apply to Parallel adaptive evolutionary algorithm(PAEA), the states of thermal unit are represented by means of real-valued strings that display continuous terms of on/off state of generating units and are involved in their minimum up and down time constraints. And the violation of other constraints are handled by repairing operator. The procedure is applied to the $10{\sim}100$ thermal unit systems, and the results show capabilities of the PAEA.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.494-496
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• 1995

This paper presents a methodology of improving a conventional numerical model in power systems using GAs and a new GAs-based model which can directly solve the real-valued optimum in the optimization procedure. The power flow which is well known to the power engineer is solved using the proposed GAs as an alternative way of the traditional optimization method. In applying GAs to the power flow, both the notions on a way of the genetic representations and a realization of the genetic operators are fully discussed to evaluate the GA's effectiveness.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.537-542
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• 2001

In recent engineering, the designer has become more and more dependent on computer simulation. But defining exact model using computer simulation is too expensive and time consuming in the complicate systems. Thus, designers often use approximation models, which express the relation between design variables and response variables. These models are called metamodel. In this paper, we introduce one of the metamodel, named Kriging. This model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. This class of interpolating model has flexibility to model response data with multiple local extreme. By reason of this multi modality, we can't use any gradient-based optimization algorithm to find global extreme value of this model. Thus we have to introduce global optimization algorithm. To do this, we introduce DE(Differential Evolution). DE algorithm is developed by Ken Price and Rainer Storn, and it has recently proven to be an efficient method for optimizing real-valued multi-modal objective functions. This algorithm is similar to GA(Genetic Algorithm) in populating points, crossing over, and mutating. But it introduces vector concept in populating process. So it is very simple and easy to use. Finally, we show how we determine Kriging metamodel and find global extreme value through two mathematical examples.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권3호
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• pp.293-307
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• 2004

본 본문에서는 다중 처리기 시스템에서 실시간 태스크를 정적으로 스케줄링하기 위한 새로운 기법을 제안한다. 태스크는 실행 시간과 마감시간을 지니고, 태스크 사이에는 선행 관계가 존재하며 이러한 사항을 태스크 그래프로 표현한다. 본 논문에서는 스케줄링을 위해 사용하는 처리기의 개수를 줄이면서 태스크들의 마감시간 지연의 총합을 최소화하는 스케줄을 생성하는 것에 목적을 둔다. 이 문제는 같은 단위로 측정할 수 없고 또한 서로 상충하는 두 가지 목적을 지닌 것이다. 그렇지만 기존 방법들은 마감시간 지연의 총합만을 최소화하려하거나 두 가지 목적을 하나의 기준으로 결합시킨 후 최적화하고자 한다. 본 논문에서는 두 개의 목적을 독립적으로 고려하며 최적화를 위하여 다목적 유전 알고리즘을 사용한다 태스크 스케줄링 문제에 적합한 문제 표현 전략, 우세 개념에 기초한 선택 연산, 그리고 교차 연산을 제시한다. 그리고 지역 개선 작업을 위해 세 개의 휴리스틱을 제안하였으며 이 것을 통해 유전 알고리즘의 수렴성을 높이고자 하였다. 성능 평가를 위해 기존에 알려진 유전 알고리즘과 4 개의 리스트 스케줄링 알고리즘과 비교한다. 평가 결과를 보면 제안한 기법이 180 개의 임의로 생성한 태스크 그래프 중에서 178 개에 대해 기존 5 개의 알고리즘과 유사하거나 더 나은 스케줄을 생성하였다.