Ant Colony System Based Drone Scheduling For Ship Emission Monitoring

Emission control area has been set up in many countries to reduce the environmental impact of vessels' emissions. However, the regulations for controlling emissions are frequently violated due to the cost of high-quality fuel. Drones currently have become an accurate and efficient way to monitor the vessels' emissions, which should be properly scheduled to cover more and higher risk of violations when facing a large number of vessels. In this paper, a scheduling model is proposed to simulate the drone scheduling monitoring problem. Due to the movement of vessels over time, the complexity of the model is too large to be solved by classical optimization methods such as CPLEX. An ant colony system algorithm is proposed to solve the scheduling problem of drones. Our method is proved to be more effective and efficient when facing a large number of vessels and drone stations in numerical experiments.