Journal of Risk Analysis and Crisis Response

Volume 7, Issue 2, July 2017, Pages 72 - 81

A Study on Marine Vessels’ Path Optimization under Typhoon Scenarios

Authors
Li Xu, Xiaobing Hu
Corresponding Author
Li Xu
Received 7 April 2017, Accepted 7 May 2017, Available Online 3 July 2017.
DOI
10.2991/jrarc.2017.7.2.3How to use a DOI?
Keywords
Marine Vessel; Real-Time Path Optimization; Typhoon; Genetic Algorithm; Receding Horizon Control
Abstract

Typhoon may cause a huge impact on the safety and costs of marine vessels on the voyage. In order to effectively solve the path optimization problem for marine vessels under typhoon scenarios, this paper proposes a hybrid algorithm integrating Genetic Algorithm (GA) with Receding Horizon Control (RHC), which considers real-time typhoon data, marine environment data including ocean currents and reefs etc., as well as safety operation requirements for marine voyage. Then, simulation experiments are conducted to test the proposed method. The experimental results indicate that the new algorithm is effective and efficient to optimize voyage paths for marine vessels under typhoon scenarios, i.e., when compared with global path optimization, the new algorithm can improve the cost-efficiency of voyage path with safety guarantee.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Risk Analysis and Crisis Response
Volume-Issue
7 - 2
Pages
72 - 81
Publication Date
2017/07/03
ISSN (Online)
2210-8505
ISSN (Print)
2210-8491
DOI
10.2991/jrarc.2017.7.2.3How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Li Xu
AU  - Xiaobing Hu
PY  - 2017
DA  - 2017/07/03
TI  - A Study on Marine Vessels’ Path Optimization under Typhoon Scenarios
JO  - Journal of Risk Analysis and Crisis Response
SP  - 72
EP  - 81
VL  - 7
IS  - 2
SN  - 2210-8505
UR  - https://doi.org/10.2991/jrarc.2017.7.2.3
DO  - 10.2991/jrarc.2017.7.2.3
ID  - Xu2017
ER  -