Abstract
The drone has become a promising tool to improve the efficiency of vessel emission monitoring in emission control areas of the part due to its high mobility. However, how to optimize the flight path of drones to improve the weighted sum of monitored vessels, i.e., drone scheduling problem (DSP), is a not yet fully researched problem. In this paper, different from the classic optimization solution method used by the literature, an efficient ant colony-based algorithm is developed to solve DSP. Given the characteristics of DSP, a hierarchical-based pheromone update strategy and partition-based pheromone management mechanism are proposed to optimize the typical ant colony algorithm. Numerical experiments not only illustrate the feasibility of using the ant colony algorithm to solve DSP, but also show that the algorithm we proposed outperforms other compared methods in terms of the solution quality and the solving speed under different problem scales.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IEEE Transactions on Intelligent Transportation Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.