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Application of Real-Coded Genetic Algorithm in Ship Weather Routing

Published online by Cambridge University Press:  25 April 2018

Hong-Bo Wang ,
Xiao-Gang Li Open the ORCID record for Xiao-Gang Li [Opens in a new window] ,
Peng-Fei Li ,
Evgeny I. Veremey  and
Margarita V. Sotnikova
Hong-Bo Wang*
Affiliation:
(State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, China)
Xiao-Gang Li
Affiliation:
(State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, China)
Peng-Fei Li
Affiliation:
(State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, China)
Evgeny I. Veremey
Affiliation:
(Faculty of Applied Mathematics and Control Processes, Saint Petersburg State University, Saint Petersburg 198504, Russia)
Margarita V. Sotnikova
Affiliation:
(Faculty of Applied Mathematics and Control Processes, Saint Petersburg State University, Saint Petersburg 198504, Russia)
*
(E-mail: wang_hongbo@jlu.edu.cn)
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Abstract

Solving the problem of ship weather routing has been always a goal of nautical navigation research and has been investigated by many scientists. The operation schedule of an oceangoing ship can be influenced by wave or wind disturbances, which complicate route planning. In this paper, we present a real-coded genetic algorithm to determine the minimum voyage route time for point-to-point problems in a dynamic environment. A fitness assignment method based on an individual's position in the sorted population is presented, which greatly simplifies the calculation of fitness value. A hybrid mutation operator is proposed to enhance the search for the optimal solution and maintain population diversity. Multi-population techniques and an elite retention strategy are employed to increase population diversity and accelerate convergence rates. The effectiveness of the algorithm is demonstrated by numerical simulation experiments.

Keywords

Weather routingReal coded genetic algorithmHybrid mutation operator

Information

Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 4 , July 2018 , pp. 989 - 1010
Copyright
Copyright © The Royal Institute of Navigation 2018 

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