Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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Distribution Analysis of Optimal Equipment Assignment Using a Genetic Algorithm

유전알고리즘을 이용하여 최적화된 방제 자원 배치안의 분포도 분석

  • 김혜진 (광운대학교 컴퓨터과학과) ;
  • 김용혁 (광운대학교 컴퓨터과학과)
  • Received : 2020.01.28
  • Accepted : 2020.04.20
  • Published : 2020.04.28
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Abstract

As a plan for oil spill accidents, research to collect and analyze optimal equipment assignments is essential. However, studies that have diversified and analyzed the optimal equipment assignments for responding to oil spill accidents have not been preceded. In response to the need for analyzing optimal equipment assignments study, we devised a genetic algorithm for optimal equipment assignments. The designed genetic algorithm yielded 10,000 optimal equipment assignments. We clustered using the k-means algorithm. As a result, the two clusters of Yeosu, Daesan, and Ulsan, which are expected to be the largest spills, were clearly identified. We also projected 16-dimensional data in two dimensions via Sammon's mapping. The projected data were analyzed for distribution. We confirmed that results of the simulation were better than those of optimal equipment assignments included in the cluster.In the future, it will be possible to implement an approximate model with excellent performance based on this study.

해양 오염사고를 대비한 계획으로, 최적화된 배치안들을 수집하여 분석하는 연구가 필수적이지만, 해양 오염사고 대응을 위한 최적을 배치안을 다양화하고 분석한 연구는 아직 선행되지 않았다. 이러한 필요성에 따라, 우리는 방제자원 배치 최적화를 위한 유전알고리즘을 고안하고 이를 통해 최적의 방제 자원 배치안을 10,000 개 도출하였다. k-평균 알고리즘으로 군집화한 결과, 예상 최대 유출지역인 여수, 대산, 울산에 대하여 두 개의 군집으로 확연히 구분되었다. 우리는 이러한 군집을 새몬 맵핑을 통해 이차원으로 사영하여 배치안의 분포도를 분석하였고, 군집에 포함되는 배치안들이 그렇지 않은 배치안보다 시뮬레이션의 결과가 우수함을 확인했다. 향후, 본 연구를 기반으로 성능이 우수한 근사모델을 구현하는 것이 가능할 것으로 보인다.

Keywords

References

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