• 한국정밀공학회지
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• 제12권9호
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• pp.95-103
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• 1995

Recently the trends toward reduction in size of industrial products have increased the application of micro drilling. But micro drilling has still much difficulty so that the needs for active control which give adaptation to controller are expanding. In this paper initial cutting condition was determined for some sorkpieces by experiment and GA-based Fuzzy controller was devised by genetic algorithms and fuzzy inference. The fuzzy inference has been applied to the various prob- lems. However the determination of the membership function is one of the difficult problem. So we introduce a genetic algorithms and propose a self-tuning method of fuzzy membership function. Based on this intelligent control, automation of micro drilling was carried out like the cutting process of skilled machinist.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2005년도 추계학술발표대회 논문집
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• pp.268-271
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• 2005

Researches based on genetic algorithms have been performed in composite laminated structures optimization since 1990. However, conventional genetic algorithms have a disadvantage that its augmentation of calculation costs. A lot of variations have been proposed to improve the performance and efficiency, and micro genetic algorithm is one of them. In this paper, micro Genetic Algorithm was employed in the optimization of laminated stiffened composite structures to maximize the linear critical buckling load and the results from both conventional genetic algorithm and micro genetic algorithm were compared.

• 대한기계학회논문집A
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• 제27권1호
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• pp.158-166
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• 2003

The paper describes the development and application of advanced evolutionary computing techniques referred to as micro genetic algorithms ($\mu$GA) in the context of engineering design optimization. The basic concept behind $\mu$GA draws from the use of small size of population irrespective of the bit string length in the representation of design variable. Such strategies also demonstrate the faster convergence capability and more savings in computational resource requirements than simple genetic algorithms (SGA). The paper first explores ten-bar truss design problems to see the optimization performance between $\mu$GA and SGA. Subsequently, $\mu$GA is applied to a realistic engineering design problem in the injection molding process optimization.

• 전자공학회논문지B
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• 제31B권4호
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• pp.40-47
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• 1994

In this paper, Micro-Genetic algorithms($\mu$-GAs) is proposed on a minimum-time path planning for robot manipulator. which is a kind of optimization algorithm. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computation burden and can`t often find the optimaul values. One way to overcome such difficulties is to apply the Micro-Genetic Algorithms, which can allow to find the optimul values, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Micro-Genetic Algorithms. The effectiveness of the proposed method is demonstrated using the 2 d.o.f plannar Robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.698-702
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• 1992

In this paper, Micro-Genetic algorithms(.mu.-GAs) is proposed on a minimum-time path planning for robot manipulator, which is a kind of optimization algorithm. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computation burden and can't often find the optimal values. One way to overcome such difficulties is to apply the Micro-Genetic Algorithms, which can allow to find the optimal values, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Micro-Genetic Algorithms. The effectiveness of the proposed method is demonstrated using the 2 d.o.f plannar Robot manipulator.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.696-702
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• 2006

Flutter characteristics of composite curved wing were investigated in this study. The efficient and robust system for the flutter optimization of general composite curved wing models has been developed using the coupled computational method based on both the standard genetic algorithm and the micro genetic algorithms. Micro genetic algorithm is used as an alternative method to overcome the relatively poor exploitation characteristics of the standard genetic algorithm. The present results show that the micro genetic algorithm is more efficient in order to find optimized lay-ups for a composite curved wing model. It is found that the flutter stability of curved wing model can be significantly increased using composite materials with proper optimum lamination design when compared to the case of isotropic wing model under the same weight condition.

• 한국산업정보학회논문지
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• 제10권4호
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• pp.54-64
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• 2005

인체 하지 근골격 시스템의 수학적 모델에 대해 최적제어 기법을 이용하여 최대 높이뛰기 운동을 재현하였다. 근육의 비선형 동적특성에 의해 순동역학 접근방법을 사용하였으며 최적제어는 최적화 프로그램인 마이크로 유전알고리즘과 VF02 비선형 최적화 프로그램을 적용하였다. 최대 높이뛰기 운동을 위한 근골격 모델에서 유전알고리즘만으로는 최적해를 얻을 수가 없었다. 유전알고리즘의 해를 비선형 최적화 프로그램의 초기 예측값으로 하여 도약시간에 따른 최적의 운동 신경자극도를 결정하였다. 이러한 접근방법은 초기의 인위적 예측값 없이 최대높이뛰기 운동에 대한 전역해를 제공하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.106.4-106
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• 2001

The current research field to find near-optimum solutions explores in a small population, which is coined as Micro-Genetic Algorithms (${\mu}$GAs), with some genetic operators. Just as in the Simple-Genetic Algorithms (SGAs), the ${\mu}$GAs work with encoding population and are implemented serially. The major difference between SGAs and ${\mu}$GAs is how to make reproductive plan for more better searching strategy due to the population choice. This paper is conducted to implement ${\mu}$GAs in order to achieve fast searching for more better evolution and associated cost evaluation in global solution space. To achieve this implementation, the Air-Borne Selection (ABS) for a new reproductive plan is developed as new strategic conception for ${\mu}$GAs. In this paper, it is shown that the ${\mu}$GAs implementation reaches a near-optimal region much earlier than the SGAs implementation. The superior ...

• 한국강구조학회 논문집
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• 제17권2호통권75호
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• pp.173-181
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• 2005

본 연구는 유한요소법과 고도화된 마이크로 유전알고리즘을 조합하여 자유 진동하는 박판 구조물에 대한 손상 규명을 다룬다. 조합된 방법에 의해 역 문제를 해결하기 위하여, 본 연구는 측정 데이터로서 구조물의 모드 형상 대신 몇 개의 고유진동수를 사용한다. 본 연구에서 제안한 방법은 손상된 요소를 탐지할 수 있을 뿐만 아니라 손상의 개수, 위치 그리고 정도를 추정할 수 있다. 제안된 방법의 타당성을 검증하기 위하여 알고리즘은 임의의 손상을 갖는 강으로 된 지유진동 박판 구조물을 대상으로 적용하였다. 기존의 단순 유전알고리즘에 비하여 본 연구에서 제안한 알고리즘은 수치적 효율성에서 큰 장점을 갖는다. 수치해석 예제들은 고유모드 대신 단지 몇 개의 고유진동수 값만으로도 마이크로 유전알고리즘은 박판의 손상을 정확히 규명할 수 있음을 보여준다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
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• pp.225-232
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• 2002

Simple genetic algorithm(SGA) has been used to optimize a lot of structural optimization problems because it can optimize non-linear problems and obtain the global solution. But, because of large evolving populations during many generations, it takes a long time to calculate fitness. Therefore this paper applied micro-genetic algorithm(μ -GA) to structural optimization and compared results of μ -GA with results of SGA. Additionally, the Paper applied μ -GA to gate optimization problem for injection molds by using simulation program CAPA.