Ship weather routing based on improved ant colony optimization algorithm
| Autor: | Dong-Qing He, Hongbo Wang, Peng-Fei Li |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Smoothness
Computer science Ant colony optimization algorithms MathematicsofComputing_NUMERICALANALYSIS 020101 civil engineering 02 engineering and technology ComputingMethodologies_ARTIFICIALINTELLIGENCE 0201 civil engineering Course (navigation) Local optimum Convergence (routing) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Point (geometry) Routing (electronic design automation) MATLAB Algorithm computer computer.programming_language |
| Zdroj: | ICPS |
| DOI: | 10.1109/icphys.2018.8387677 |
| Popis: | In this paper, the ant colony optimization (ACO) algorithm is introduced into the ship weather routing problem, aiming at finding the optimal route for transoceanic ships quickly, efficiently and accurately. The author has improved the traditional ACO algorithm in two aspects. Firstly, the ant moving rule is modified so that ants are more purposeful when searching for route points. Then, pheromone updating rule is improved to increase algorithm convergence speed and avoid local optima. Finally, the improved ACO algorithm is applied to the route optimization simulation experiment under the weather conditions. It has been verified that the improved ACO algorithm has better performance in route smoothness and convergence speed. The simulation results of MATLAB show that the algorithm can not only find a shorter distance route from starting point to end, but also ensure that the navigation time of the route is relatively short. Besides, the optimized route planned by the algorithm can also avoid the dangerous areas encountered in the course of navigation in time and ensure the safety of the ship at sea. |
| Databáze: | OpenAIRE |
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