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9 September 2019 Application of Ant Colony Algorithms in Path Planning of Ocean Survey
Hongtao Yu, Sen Wang, Yan Bao
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Abstract

Yu, H.-T.; Wang, S., and Bao, Y., 2019. Application of ant colony algorithms in path planning of ocean survey. In: Gong, D.; Zhu, H., and Liu, R.(eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 121–124. Coconut Creek (Florida), ISSN 0749-0208.

Due to the existence of multiple constraints and optimization objectives, the path planning of ocean survey is very difficult. In this paper, ant colony algorithm is applied to the path planning of ocean survey. Considering the coverage of ant colony algorithm, the path planning of ocean survey is carried out, the competitive decision of ocean boundary is made, and the initial solution is created. In the path planning of ocean survey, the local search scope is limited to the K-nearest neighborhood of the network, only the most possible spatial neighborhood is searched, and the quality of the solution is improved iteratively. The performance of the algorithm is tested by using ocean survey path planning. The experimental results show that the proposed method can solve the competitive decision-making problem of 6 400 survey paths in 15 minutes. The quality of the solution is 10.8% better than that of ArcGIS, and the computing time is about 21.2%.

©Coastal Education and Research Foundation, Inc. 2019
Hongtao Yu, Sen Wang, and Yan Bao "Application of Ant Colony Algorithms in Path Planning of Ocean Survey," Journal of Coastal Research 94(sp1), 121-124, (9 September 2019). https://doi.org/10.2112/SI94-023.1
Received: 1 January 2019; Accepted: 12 May 2019; Published: 9 September 2019
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KEYWORDS
ant colony algorithms
large data mining algorithms
Path planning for ocean survey
problem competition decision
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