Designing Patrol Ship Routes Based on Multi Data Sources for Marine Environment

Abstract

Maritime transportation demand has increased in the past decades and managing navigation safety has become key in maritime management and decision-making. However, the environmental diversity and limitations of the maritime risk model in large to small regions render maritime management more complex. Therefore, by considering different factors and limitations, ship path planning in a large-scale space in three regions of the South Korean Ocean is proposed herein. Additionally, an innovative for calculating a risk factor is performed, and a collaborative scheme with different objectives is developed. The developed algorithm focuses on maximizing coverage and minimizing travel distance, and a genetic algorithm is used as a backbone to solve the problems encountered. Results indicate that the developed algorithm reduces the travel distance, increases the area coverage, and reduces the possible risks by -29.2%, 195.5%, and 91.5%, respectively, as compared with the previous patrol ship route schedule in 14 days, which is determined by the captain’s experience. The results of our computational study can facilitate future endeavors related to maritime safety and the development of path planning for patrol ships.