한국경영과학회지 (Journal of the Korean Operations Research and Management Science Society)

  • 제23권1호
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  • Pages.1-16
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  • 1998
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  • 1225-1119(pISSN)
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  • 2733-4759(eISSN)
한국경영과학회 (The Korean Operations Research and Management Science Society)
권호 표지

유전자 알고리듬과 K-평균법을 이용한 지역 분할

Zone Clustering Using a Genetic Algorithm and K-Means

  • 발행 : 1998.03.01
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초록

The zone clustering problem arising from several area such as deciding the optimal location of ambient measuring stations is to devide the 2-dimensional area into several sub areas in which included individual zone shows simimlar properties. In general, the optimal solution of this problem is very hard to obtain. Therefore, instead of finding an optimal solution, the generation of near optimal solution within the limited time is more meaningful. In this study, the combination of a genetic algorithm and the modified k-means method is used to obtain the near optimal solution. To exploit the genetic algorithm effectively, a representation of chromsomes and appropriate genetic operators are proposed. The k-means method which is originally devised to solve the object clustering problem is modified to improve the solutions obtained from the genetic algorithm. The experiment shows that the proposed method generates the near optimal solution efficiently.

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참고문헌

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