• Title/Summary/Keyword: 전략적 진화 연산자

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A Study for searching optimized combination of Spent light water reactor fuel to reuse as heavy water reactor fuel by using evolutionary algorithm (진화 알고리즘을 이용한 경수로 폐연료의 중수로 재사용을 위한 최적 조합 탐색에 관한 연구)

  • 안종일;정경숙;정태충
    • Journal of Intelligence and Information Systems
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    • v.3 no.2
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    • pp.1-9
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    • 1997
  • These papers propose an evolutionary algorithm for re-using output of waste fuel of light water reactor system in nuclear power plants. Evolutionary algorithm is useful for optimization of the large space problem. The wastes contain several re-useable elements, and they should be carefully selected and blended to satisfy requirements as input material to the heavy water nuclear reactor system. This problem belongs to a NP-hard like the 0/1 Knapsack problem. Two evolutionary strategies are used as a, pp.oximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method, which performs the feasible teat and solution evaluation by using the vectorized data in problem. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.

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Design of Intelligent Fuzzy Controller for Nonlinear System Using Genetic Algorithm (유전 알고리즘을 이용한 비선형 시스템의 지능형 퍼지 제어기 설계)

  • 김문환;주영훈;박진배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.247-250
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    • 2004
  • 본 논문은 비선형 시스템의 새로운 퍼지 제어기 설계 기법을 제안한다. 퍼지 제어기는 비선형 시스템을 제어하는데 많이 사용되는 기법 중에 하나이다. 퍼지 제어기를 설계하는 것은 시스템에 대한 깊은 수학적인 접근이 필요로 하기 때문에 수학적 배경 없이 설계하기 힘들다. 본 논문에서는 이를 해결하기 위해 길은 수학적인 접근이 아닌 지능적인 접근 방법을 사용하여 안정화된 퍼지 제어기의 설계하는 기법을 제안한다. 제안된 기법은 퍼지 제어기의 안정화 조건을 만족시키는 제어 파라메터를 전략 기반 유전 알고리즘을 사용하여 동정한다. 전략 기반 유전 알고리즘은 제어기의 안정화 조건을 만족시키는 해를 찾기 위해 전략적으로 교차와 돌연변이를 변화시킨다. 최종적으로 모의 실험을 통해 제안된 기법의 우수성을 확인한다.

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Fuzzy Controller Design of 2 D.O.F of Wheeled Mobile Robot using Niche Meta Genetic Algorithm (Niche Meta 유전 알고리즘을 이용한 2자유도 이동 로봇의 퍼지 제어기 설계)

  • Kim Sung-Hoe;Kim Ki-Yeoul
    • The Journal of Information Technology
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    • v.5 no.4
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    • pp.73-79
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    • 2002
  • In this paper, I will propose the Niche-Meta Genetic Algorithm that has a multi-mutation operator for design of fuzzy controller. The gene in the proposed algorithm is formed by several parameters that represent the crossover rate, mutation rate and input-output membership functions. The optimization of fuzzy membership function is performed with local search on sub-population and the optimal structure is constructed with global search on total-population. The multi-mutation is selected under basis of the result of local evolution. A simulation for 2 D.O.F wheeled-mobile robot is showed to prove the efficiency of the proposed algorithm

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Vector Heuristic into Evolutionary Algorithms for Combinatorial Optimization Problems (진화 알고리즘에서의 벡터 휴리스틱을 이용한 조합 최적화 문제 해결에 관한 연구)

  • Ahn, Jong-Il;Jung, Kyung-Sook;Chung, Tae-Choong
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.6
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    • pp.1550-1556
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    • 1997
  • In this paper, we apply the evolutionary algorithm to the combinatorial optimization problem. Evolutionary algorithm useful for the optimization of the large space problem. This paper propose a method for the reuse of wastes of light water in atomic reactor system. These wastes contain several reusable elements, and they should be carefully selected and blended to satisfy requirements as an input material to the heavy water atomic reactor system. This problem belongs to an NP-hard like the 0/1 knapsack problem. Two evolutionary strategies are used as approximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method which perform the feasible test and solution evaluation by using the vectored knowledge in problem domain. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.

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