• 제목/요약/키워드: micro-genetic algorithm

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무향 Rural Postman Problem 해법을 위한 마이크로 유전자 알고리즘 (Micro-Genetic Algorithm for Undirected Rural Postman Problem)

  • 강명주
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2015년도 제51차 동계학술대회논문집 23권1호
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    • pp.167-168
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    • 2015
  • 유전자 알고리즘은 문제 크기가 커짐에 따라 해집합이 폭발적으로 늘어나 최적해를 찾기 힘든 최적화 문제에 주로 적용되는 알고리즘으로, 최근에는 지리정보시스템(GIS)의 경로 최적화 문제, 게임에서의 길찾기, 인공지능에 많이 적용되고 있다. 마이크로 유전자 알고리즘은 일반 유전자 알고리즘에 비해 작은 크기의 모집단을 사용함으로써 알고리즘의 효율을 높일 수 있는 장점이 있다. 따라서, 본 논문에서는 무향 Rural Postman Problem 해법으로 마이크로 유전자 알고리즘의 적용 방법을 제안한다.

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마이크로 밀링 머신의 저진동.경량화를 위한 구조 최적설계 (Structural Design Optimization of a Micro Milling Machine for Minimum Weight and Vibrations)

  • 장성현;권봉철;최영휴;박종권
    • 한국공작기계학회논문집
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    • 제18권1호
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    • pp.103-109
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    • 2009
  • This paper presents structural design optimization of a micro milling machine for minimum weight and compliance using a genetic algorithm with dynamic penalty function. The optimization procedure consists of two design stages, which are the static and dynamic design optimization stages. The design problem, in this study, is to find out thickness of structural members which minimize the weight, the static compliance and the dynamic compliance of the micro milling machine under several constraints such as dimensional constraints, maximum compliance limit, and safety factor criterion. Optimization results showed a great reduction in the static and dynamic compliances at the spindle nose of the micro milling machine in spite of a little decrease in the machine weight.

유전알고리즘을 이용한 대형 디젤 엔진 운전 조건 최적화 (Optimization of Heavy-Duty Diesel Engine Operating Parameters Using Micro-Genetic Algorithms)

  • 김만식
    • 한국자동차공학회논문집
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    • 제13권2호
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    • pp.101-107
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    • 2005
  • In this paper, optimized operating parameters were found using multi-dimensional engine simulation software (KIVA-3V) and micro-genetic algorithm for heavy duty diesel engine. The engine operating condition considered was at 1,737 rev/min and 57 % load. Engine simulation model was validated using an engine equipped with a high pressure electronic unit injector (HEUI) system. Three important parameters were used for the optimization - boost pressure, EGR rate and start of injection timing. Numerical optimization identified HCCI-like combustion characteristics showing significant improvements for the soot and $NO_X$ emissions. The optimized soot and $NO_X$ emissions were reduced to 0.005 g/kW-hr and 1.33 g/kW-hr, respectively. Moreover, the optimum results met EPA 2007 mandates at the operating point considered.

최적화 기법에 의한 인체 하지 근골격 시스템의 최적제어 모델 개발 (An optimization approach for the optimal control model of human lower extremity musculoskeletal system)

  • 김선필
    • 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.

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순차적 실험계획법과 마이크로 유전알고리즘을 이용한 최적화 알고리즘 개발 (Development of Optimization Algorithm Using Sequential Design of Experiments and Micro-Genetic Algorithm)

  • 이정환;서명원
    • 대한기계학회논문집A
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    • 제38권5호
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    • pp.489-495
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    • 2014
  • 마이크로 유전알고리즘은 적은 수의 개체 사용 및 무작위 개체 구성을 통한 돌연변이 기능 대체의 특징을 갖는 진화연산을 수행하여 일반적인 유전알고리즘이 갖는 각 세대당 많은 계산 량이 요구되는 단점을 극복하고자 하였다. 이러한 마이크로 알고리즘은 특히 설계변수가 3~5 개를 갖는 문제에 효율적이라는 것이 많은 연구자들에 의하여 알려졌다. 따라서 본 연구의 목적은 순차적 실험계획법과 마이크로 유전알고리즘을 이용한 최적화 알고리즘을 개발하는 것이며, 이를 수학예제와 구조물 문제에 적용하여 실용성을 확인하고자 한다. 순차적 실험계획법은 저자들의 선행연구에서 제안되었으며, 실험계획법과 반응표면법을 이용하는 근사최적화 기법에 의한 시행착오적인 반복과정을 최소화하고자 하는 방법으로써, 행렬실험과 평균분석을 반복 적용하는 개념이다.

NSGA-II를 이용한 마이크로 프로펠러 수차 블레이드 최적화 (Optimization of Micro Hydro Propeller Turbine blade using NSGA-II)

  • 김병곤
    • 한국유체기계학회 논문집
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    • 제17권4호
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    • pp.19-29
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    • 2014
  • In addition to the development of micro hydro turbine, the challenge in micro hydro turbine design as sustainable hydro devices is focused on the optimization of turbine runner blade which have decisive effect on the turbine performance to reach higher efficiency. A multi-objective optimization method to optimize the performance of runner blade of propeller turbine for micro turbine has been studied. For the initial design of planar blade cascade, singularity distribution method and the combination of the Bezier curve parametric technology is used. A non-dominated sorting genetic algorithm II(NSGA II) is developed based on the multi-objective optimization design method. The comparision with model test show that the blade charachteristics is optimized by NSGA-II has a good efficiency and load distribution. From model test and scale up calculation, the maximum prototype efficiency of the runner blade reaches as high as 90.87%.

Optimum Design of the Power Yacht Based on Micro-Genetic Algorithm

  • Park, Joo-Shin;Kim, Yun-Young
    • 한국항해항만학회지
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    • 제33권9호
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    • pp.635-644
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    • 2009
  • The optimum design of power yacht belongs to the nonlinear constrained optimization problems. The determination of scantlings for the bow structure is a very important issue with in the whole structural design process. The derived design results are obtained by the use of real-coded micro-genetic algorithm including evaluation from Lloyd's Register small craft guideline, so that the nominal limiting stress requirement can be satisfied. In this study, the minimum volume design of bow structure on the power yacht was carried out based on the finite element analysis. The target model for optimum design and local structural analysis is the bow structure of a power yacht. The volume of bow structure and the main dimensions of structural members are chosen as an objective function and design variable, respectively. During optimization procedure, finite element analysis was performed to determine the constraint parameters at each iteration step of the optimization loop. optimization results were compared with a pre-existing design and it was possible to reduce approximately 19 percents of the total steel volume of bow structure from the previous design for the power yacht.

마이크로 유전알고리즘을 이용한 적운물리과정 모수 최적화에 따른 여름철 강수예측성능 개선 (The Improvement of Summer Season Precipitation Predictability by Optimizing the Parameters in Cumulus Parameterization Using Micro-Genetic Algorithm)

  • 장지연;이용희;최현주
    • 대기
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    • 제30권4호
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    • pp.335-346
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    • 2020
  • Three free parameters included in a cumulus parameterization are optimized by using micro-genetic algorithm for three precipitation cases occurred in the Korea Peninsula during the summer season in order to reduce biases in a regional model associated with the uncertainties of the parameters and thus to improve the predictability of precipitation. The first parameter is the one that determines the threshold in convective trigger condition. The second parameter is the one that determines boundary layer forcing in convective closure. Finally, the third parameter is the one used in calculating conversion parameter determining the fraction of condensate converted to convective precipitation. Optimized parameters reduce the occurrence of convections by suppressing the trigger of convection. The reduced convection occurrence decreases light precipitation but increases heavy precipitation. The sensitivity experiments are conducted to examine the effects of the optimized parameters on the predictability of precipitation. The predictability of precipitation is the best when the three optimized parameters are applied to the parameterization at the same time. The first parameter most dominantly affects the predictability of precipitation. Short-range forecasts for July 2018 are also conducted to statistically assess the precipitation predictability. It is found that the predictability of precipitation is consistently improved with the optimized parameters.

구조물의 설계 최적화를 위한 메트로폴리스 유전알고리즘의 개발 및 적용 (Development and Application of Metropolis Genetic Algorithm for the Structural Design Optimization)

  • 박균빈;류연선;김정태;조현만
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2003년도 가을 학술발표회 논문집
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    • pp.115-122
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    • 2003
  • A Metropolis genetic algorithm(MGA) is developed and applied for the structural design optimization. In MGA favorable features of Metropolis algorithm in simulated annealing(SA) are incorporated in simple genetic algorithm(SGA), so that the MGA alleviates the disadvantage of finding imprecise solution in SGA and time-consuming computation in SA. Performances of MGA are compared with those of conventional algorithms such as Holland's SGA, Krishnakumar's micro genetic algorithm(μGA), and Kirkpatrick's SA. Typical numerical examples are used to evaluate the favorable features and applicability of MGA From the theoretical evaluation and numerical experience, it is concluded that the proposed MGA is a reliable and efficient tool for structural design optimization.

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