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Symmetry 2019, 11(1), 32;

Optimal Rescue Ship Locations Using Image Processing and Clustering

Department of Marine Science and Production, Kunsan National University, Gunsan 54150, Jeonbuk, Korea
Mokpo Maritime University, Mokpo 58628, Jeonnam, Korea
Author to whom correspondence should be addressed.
Received: 15 October 2018 / Revised: 7 December 2018 / Accepted: 11 December 2018 / Published: 2 January 2019
(This article belongs to the Special Issue Symmetry in Computing Theory and Application)
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Currently, globalization of the world economy has also resulted in a shipping volume increase. However, this growth in maritime traffic has led to increased risk of marine accidents. These accidents have a higher probability of occurring in regions where geographical features such as islands are present. Further, the positioning of rescue ships in a particular ocean region with a high level of maritime activity is critical for rescue operations. This paper proposes a method for determining an optimal set of locations for stationing rescue ships in an ocean region with numerous accident sites, such as in the Wando islands of South Korea. The computational challenge in this problem is identified as the positioning of numerous islands of varying sizes located in the region. Thus, the proposed method combines a clustering-based optimization method and an image processing approach that incorporates flood filling to calculate the shortest pixel value between two points in the ocean that detours around the islands. Experimental results indicate that the proposed method reduces the distance between rescue ships and each accident site by 5.0 km compared to the original rescue ship locations. Thus, rescue time is reduced. View Full-Text
Keywords: clustering-based optimization; location optimization; flood-filling algorithm; marine accident; rescue ship; shortest distance clustering-based optimization; location optimization; flood-filling algorithm; marine accident; rescue ship; shortest distance

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Jung, C.-Y.; Yoo, S.-L. Optimal Rescue Ship Locations Using Image Processing and Clustering. Symmetry 2019, 11, 32.

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