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http://dx.doi.org/10.15207/JKCS.2020.11.4.011

Distribution Analysis of Optimal Equipment Assignment Using a Genetic Algorithm  

Kim, Hye-Jin (Dept. Computer Science, Kwangwoon University)
Kim, Yong-Hyuk (Dept. Computer Science, Kwangwoon University)
Publication Information
Journal of the Korea Convergence Society / v.11, no.4, 2020 , pp. 11-16 More about this Journal
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.
Keywords
Convergence; Genetic algorithm; Clustering; Sammon's mapping; Optimal resource allocation;
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