Journal of the Korea Society for Simulation (한국시뮬레이션학회논문지)

The Korea Society for Simulation (한국시뮬레이션학회)
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The Genetic Algorithm using Variable Chromosome with Chromosome Attachment for decision making model

의사결정 모델을 위한 염색체 비분리를 적용한 가변 염색체 유전 알고리즘

  • Received : 2017.07.13
  • Accepted : 2017.11.24
  • Published : 2017.12.31
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Abstract

The Genetic Algorithm(GA) is a global search algorithm based on biological genetics. It is widely used in various fields such as industrial applications, artificial neural networks, web applications and defense industry. However, conventional Genetic Algorithm has difficulty maintaining feasibility in complicated situations due to its fixed number of chromosomes. This study proposes the Genetic Algorithm using variable chromosome with chromosome attachment. And in order to verify the implication of changing number of chromosomes in the simulation, it applies the Genetic Algorithm using variable chromosome with chromosome attachment to antisubmarine High Value Unit(HVU) escort mission simulation. As a result, the Genetic Algorithm using variable chromosome has produced complex strategies faster than the conventional method, indicating the increase of the number of chromosome during the process.

유전 알고리즘은 생물 유전학에 기본 이론을 두는 전역 탐색 알고리즘으로, 산업, 뉴럴 네트워크, 웹, 그리고 국방 등의 분야에서 활발히 사용되고 있다. 하지만 기존의 유전 알고리즘은 염색체의 개수가 고정되어 있는 형태여서 시뮬레이션 도중 초기에 주어진 상황보다 더 복잡한 상황이 주어질 수 있는 경우에는 적용이 힘들다는 한계점이 존재한다. 본 연구에서는 이를 극복하기 위해서 염색체 비분리를 적용한 가변 염색체 유전 알고리즘을 제안하였다. 그리고 염색체 수의 변화가 시뮬레이션 결과에 영향을 미치는 것을 확인하기 위하여 대 잠수함 HVU 호위 임무 시뮬레이션에 염색체 비분리를 적용한 가변 염색체 유전 알고리즘을 적용하였다. 시뮬레이션 결과 기존의 유전 알고리즘과는 달리 가변 염색체 유전 알고리즘에서는 더 복잡한 전술이 더 일찍 등장하였으며, 그에 따라 염색체 수가 증가하는 방향으로 진화가 일어나는 것을 확인할 수 있었다.

Keywords

References

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