• 제목/요약/키워드: Multi Objective Genetic Algorithm

검색결과 311건 처리시간 0.026초

인접건물의 준능동 퍼지제어를 위한 유전자알고리즘 기반 다목적 최적설계 (Multi-objective Optimal Design using Genetic Algorithm for Semi-active Fuzzy Control of Adjacent Buildings)

  • 김현수
    • 한국산학기술학회논문지
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    • 제17권1호
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    • pp.219-224
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    • 2016
  • 본 연구에서는 지진하중을 받는 인접한 건물의 진동제어를 위한 준능동 제어장치의 제어성능을 검토하였다. 준능동 제어장치로는 MR 감쇠기를 사용하였다. MR 감쇠기로 연결된 인접한 건물을 효과적으로 제어하기 위하여 퍼지제어알고리즘을 사용하였다. MR 감쇠기로 연결된 인접한 건물의 제어시 한쪽 건물의 응답을 저감시키는 것은 다른 한 쪽 건물의 응답을 증가시키는 효과를 가져온다. 따라서 연결된 건물의 제어는 서로 상충되는 특성이 있기 때문에 다목적 최적화문제로 귀결된다. 따라서 본 연구에서는 다목적 유전자알고리즘을 사용하여 MR 감쇠기를 제어하는 퍼지제어알고리즘을 최적화하였다. 수치해석을 통하여 준능동 MR 감쇠기를 이용한 인접건물의 연결제어효과를 검토하였고 매우 우수한 성능을 나타내는 것을 확인하였다.

적응형 스마트 공유 TMD의 MIMO 제어알고리즘개발 (Development of Multi-Input Multi-Output Control Algorithm for Adaptive Smart Shared TMD)

  • 김현수;강주원
    • 한국공간구조학회논문집
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    • 제15권2호
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    • pp.105-112
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    • 2015
  • A shared tuned mass damper (STMD) was proposed in previous research for reduction of dynamic responses of the adjacent buildings subjected to earthquake loads. A single STMD can provide similar control performance in comparison with two traditional TMDs. In previous research, a passive damper was used to connect the STMD with adjacent buildings. In this study, a smart magnetorheological (MR) damper was used instead of a passive damper to compose an adaptive smart STMD (ASTMD). Control performance of the ASTMD was investigated by numerical analyses. For this purpose, two 8-story buildings were used as example structures. Multi-input multi-output (MIMO) fuzzy logic controller (FLC) was used to control the command voltages sent to two MR dampers. The MIMO FLC was optimized by a multi-objective genetic algorithm. Numerical analyses showed that the ASTMD can effectively control dynamic responses of adjacent buildings subjected to earthquake excitations in comparison with a passive STMD.

가중합 유전자 알고리즘 기반의 다목적 최적화를 이용한 톤 삽입 PAPR 저감 기법 (A Tone Injection PAPR Reduction Method using Multi-objective Optimization based on Weighted-sum Genetic Algorithm)

  • 박순규;이원철
    • 한국통신학회논문지
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    • 제34권2C호
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    • pp.217-225
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    • 2009
  • OFDM(Orthogonal Frequency Division Multiplexing) 시스템을 포함한 다중 반송파 시스템에서 발생하는 PAPR(Peak-to-Average Power Ratio)을 감소시키기 위해 특정 톤 위치에 새로운 톤을 삽입하는 톤 삽입 기법은 성상도를 확장하여 평균 신호전력 대비 최대 신호 전력을 감소시키는 기법이다. 이러한 톤 삽입 기법은 최적의 PAPR 저감 성능을 얻기 위한 삽입 톤 결정을 위해 많은 탐색 연산량을 필요로 함과 동시에 높은 전력상승의 문제를 야기하는 반면, 전력상승을 고려하여 삽입 톤을 결정하면 사용 가능한 톤 삽입 신호가 제한됨에 따라 PAPR 저감 성능이 낮아진다. 따라서 본 논문에서는 기존의 톤 삽입 기법이 갖는 상충적인 목적들을 다목적 최적화 기법에 적용하여 PAPR 저감 성능과 전력상승을 절충하여 상호간의 유연한 조절이 가능한 가중함 유전자 알고리즘 기반의 톤 삽입 기법을 제안한다 모의 실험을 통하여 제안한 가중함 유전자 알고리즘 기반의 톤 삽입 방법은 PAPR과 전력상승의 문제를 사용자의 의사를 반영하는 가중치에 따라 적절하게 조절할 수 있음을 확인하였다.

NSGA-II를 통한 딤플채널의 다중목적함수 최적화 (Multi-Objective Optimization of a Dimpled Channel Using NSGA-II)

  • 이기돈;압두스 사마드;김광용
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2008년도 춘계학술대회논문집
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    • pp.113-116
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    • 2008
  • This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

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다목적 유전자알고리즘을 이용한 Tank 모형 매개변수 최적화(I): 방법론과 모형구축 (Optimization of Tank Model Parameters Using Multi-Objective Genetic Algorithm (I): Methodology and Model Formulation)

  • 김태순;정일원;구보영;배덕효
    • 한국수자원학회논문집
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    • 제40권9호
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    • pp.677-685
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    • 2007
  • 본 연구의 목적은 개념적인 강우-유출모형인 Tank 모형의 매개변수를 산정하기 위한 다목적 유전자알고리즘의 적용성을 평가하는 것이다. 다목적 유전자알고리즘 기법으로는 최근에 가장 많이 사용되는 기법중의 하나인 NSGA-II를 채택하여 Tank 모형과 결합하였으며, 4가지 목적함수(유출용적오차, 평균제곱근 오차, 고수유량 평균제곱근 오차 및 저수유량 평균제곱근 오차)값을 최소화하는 형태의 목적함수를 적용하였다. NSGA-II는 목적함수의 개수가 많아지면 한 번의 실행에 의해 굉장히 많은 수의 파레토최적해를 구하는 단점을 가지고 있기 때문에 구해진 파레토최적해 중에서 어떤 해가 최우선해 인지를 결정해야 할 필요가 있으며, 이러한 고차원적인 의사결정을 위하여 선호적순서화(preference ordering) 기법을 적용하였다. NSGA-II를 이용하여 Tank모형의 매개변수를 추정할 때 초기조건이 최적화과정에 미칠 수 있는 영향을 최소화하기 위해 세대수(generation number)와 개체군의 크기(population size)에 대한 민감도분석을 수행하였다. 분석결과 Tank모형의 매개변수 최적화를 위한 세대수와 개체군 크기의 초기 값을 각각 900번과 1000개로 선정하는 것이 적합한 것으로 나타났다.

Genetic Algorithm Based Design Optimization of a Six Phase Induction Motor

  • Fazlipour, Z.;Kianinezhad, R.;Razaz, M.
    • Journal of Electrical Engineering and Technology
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    • 제10권3호
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    • pp.1007-1014
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    • 2015
  • An optimally designed six-phase induction motor (6PIM) is compared with an initial design induction motor having the same ratings. The Genetic Algorithm (GA) method is used for optimization and multi objective function is considered. Comparison of the optimum design with the initial design reveals that better performance can be obtained by a simple optimization method. Also in this paper each design of 6PIM, is simulated by MAXWELL_2D. The obtained simulation results are compared in order to find the most suitable solution for the specified application, considering the influence of each design upon the motor performance. Construction a 6PIM based on the information obtained from GA method has been done. Quality parameters of the designed motors, such as: efficiency, power losses and power factor measured and optimal design has been evaluated. Laboratory tests have proven the correctness of optimal design.

Optimizing Design Variables for High Efficiency Induction Motor Considering Cost Effect by Using Genetic Algorithm

  • Han, Pil-Wan;Seo, Un-Jae;Choi, Jae-Hak;Chun, Yon-Do;Koo, Dae-Hyun;Lee, Ju
    • Journal of Electrical Engineering and Technology
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    • 제7권6호
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    • pp.948-953
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    • 2012
  • The characteristics of an induction motor vary with the number of parameters and the performance relationship between the parameters also is implicit. In case of the induction motor design, we generally should estimate many objective physical quantities in the optimization procedure. In this article, the multi objective design optimization based on genetic algorithm is applied for the three phase induction motor. The efficiency, starting torque, and material cost are selected for the objectives. The validity of the design results is also clarified by comparison between calculated results and measured ones.

유전 알고리즘을 활용한 무인기의 다중 임무 계획 최적화 (Multi-mission Scheduling Optimization of UAV Using Genetic Algorithm)

  • 박지훈;민찬오;이대우;장우혁
    • 한국항공운항학회지
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    • 제26권2호
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    • pp.54-60
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    • 2018
  • This paper contains the multi-mission scheduling optimization of UAV within a given operating time. Mission scheduling optimization problem is one of combinatorial optimization, and it has been shown to be NP-hard(non-deterministic polynomial-time hardness). In this problem, as the size of the problem increases, the computation time increases dramatically. So, we applied the genetic algorithm to this problem. For the application, we set the mission scenario, objective function, and constraints, and then, performed simulation with MATLAB. After 1000 case simulation, we evaluate the optimality and computing time in comparison with global optimum from MILP(Mixed Integer Linear Programming).

유전 알고리듬을 이용한 압전센서의 전극형상 최적화 (Electrode Shape Optimization of Piezo Sensors Using Genetic Algorithm)

  • 이기문;박현철;박철휴
    • 대한기계학회논문집A
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    • 제30권6호
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    • pp.698-704
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    • 2006
  • This paper presents an electrode shape design method for the multi-mode sensors that could deteict the selected structural multiple modes. The structure used for this study is an isotropic cantilever beam type with a PVDF (polyvinylidene fluoride) which is bonded onto the structure as a sensor. The shape optimization problem is solved by using Genetic Algorithm (GA) with an appropriate objective function. The performance of analytical optimal shape sensor is compared with that of experimental work. The results show that the, obtained electrode shape sensors have good performance to detect the multiple vibration modes simultaneously.

반응표면법-역전파신경망을 이용한 AA5052 판재 점진성형 공정변수 모델링 및 유전 알고리즘을 이용한 다목적 최적화 (Modeling of AA5052 Sheet Incremental Sheet Forming Process Using RSM-BPNN and Multi-optimization Using Genetic Algorithms)

  • 오세현;샤오샤오;김영석
    • 소성∙가공
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    • 제30권3호
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    • pp.125-133
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    • 2021
  • In this study, response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goal of optimization is to determine the maximum forming angle and minimum surface roughness, while varying the production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model and BPNN model to model the variations in the forming angle and surface roughness based on variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process the GA. The results showed that RSM and BPNN can be effectively used to control the forming angle and surface roughness. The optimized Pareto front produced by the GA can be utilized as a rational design guide for practical applications of AA5052 in the ISF process