정보처리학회논문지A (The KIPS Transactions:PartA)

한국정보처리학회 (Korea Information Processing Society)
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퍼지 논리를 이용한 병렬 유전 알고리즘

Parallel Genetic Algorithm using Fuzzy Logic

  • 안영화 (강남대학교 컴퓨터미디어공학부) ;
  • 권기호 (성균관대학교 정신통신학부)
  • 발행 : 2006.02.01
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초록

유전 알고리즘은 자연 선택과 유전적 성질에 기반을 둔 알고리즘으로 기존 방법으로는 쉽게 해결할 수 없는 어려운 문제에서도 성공적으로 적용되었다. 기존의 유전 알고리즘은 해 집단이 큰 경우 시간이 많이 걸리는 문제점이 있다. 병렬 유전 알고리즘은 이러한 문제를 해결하기 위하여 제안된 기존의 유전 알고리즘의 확장이라 할 수 있다. 병렬 유전 알고리즘에서 중요한 요소는 이주와 유전 연산으로 이를 적절하게 설계함으로서 좋은 결과를 얻을 수 있다. 본 논문에서는 퍼지 논리를 이용하여 기존의 병렬 유전 알고리즘을 개선하고자 한다.

Genetic algorithms(GA), which are based on the idea of natural selection and natural genetics, have proven successful in solving difficult problems that are not easily solved through conventional methods. The classical GA has the problem to spend much time when population is large. Parallel genetic algorithm(PGA) is an extension of the classical GA. The important aspect in PGA is migration and GA operation. This paper presents PGAs that use fuzzy logic. Experimental results show that the proposed methods exhibit good performance compared to the classical method.

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참고문헌

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