A Mathematical Modeling and an Optimization Algorithm for Marine Ship Route Planning

Author:

Huang Lili1ORCID

Affiliation:

1. Zhengzhou Tourism College, Zhengzhou, Henan 451464, China

Abstract

In order to solve the problem of ship route planning at sea, we reduce the economic cost of ship navigation planning and improve the efficiency of ship navigation. As a result, the goal of this work is to delve into the mathematical modeling and the best algorithm for marine ship route planning. To begin, a mathematical model of ship route planning is created, taking into account the impact of nonuniformity in the offshore wind field on ship route planning, with the shortest ship sailing time as the goal. Based on the mathematical model, the ant colony algorithm is used to optimize the initial route of the ship. Finally, through the optimization of the ant colony algorithm, the optimal route with the shortest total length and the smaller steering angle is obtained, and the optimal ship navigation planning scheme is obtained. The simulation results show that, when compared to artificial intelligence and genetic algorithms, the optimization algorithm suggested in this research produces the best ship route planning outcomes and has the lowest economic cost, which may effectively increase the efficiency of ship route work.

Publisher

Hindawi Limited

Subject

General Mathematics

Reference17 articles.

1. Route planning of intelligent ships considering navigation environment factors;W. Pan;Journal of Shanghai Maritime University,2021

2. Improved genetic algorithm-based ship route planning considering ship maneuverability constraints;L. P. Wang;Journal of Harbin Engineering University,2021

3. Route planning of vessels with ant colony algorithm and massive AIS data;X. X. Yao;Journal of Transport Information and Safety,2019

4. Automatic ship route planning based on deep reinforcement learning;Z. H. Han;Navigation of China,2021

5. Dynamic route planning method for intelligent ships considering complex meteorological changes;G. X. Wang;Journal of Shanghai Maritime University,2021

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