An Integrated Approach Using Ant Colony Optimization and Genetic Algorithms for Fuel-Efficient and Safe Ship Routing Under Dynamic Weather Conditions

In recent years, the maritime industry has faced increasing pressure to optimize routes for better fuel efficiency and to ensure the safety of vessels amidst dynamic weather conditions. This paper introduces an innovative approach that leverages the synergies of Ant Colony Optimization (ACO) and Genetic Algorithms (GAs) to tackle the issue of fuel-efficient and safe ship routing. The proposed method calculates the cruising speed by considering weather conditions such as wind speed, wind direction, wave height, and wave direction. The key factor affecting fuel consumption is identified as ship speed, and the proposed algorithm determines the optimal cruising speeds and solves the routing problem. The experimental results indicate that, despite an increase in the total route length, the ACO method provides routes with lower fuel consumption compared to the traditional Great Circle Route method.