An Ant Colony Algorithm for efficient ship routing

With the substantial rising of international oil price and global warming on the rise, how to reduce operational fuel consumption and decrease air pollution has become one of the pursued goals of green ship. Ship route planning is an indispensible part of the ship navigation process, especially in transoceanic crossing ship routing. The soundness of ship routing not only affects the safety of ship navigation but also the operation economy and environmental protection. This research is based on the platform of Electronic Chart Display and Information System (ECDIS), and founded on Ant Colony Algorithm (ACA) combined with the concept of Genetic Algorithm (GA), to model living organisms optimization behaviour to perform efficient ship route planning in transoceanic crossing. Besides the realization of route planning automation, ship routing will achieve the goal of optimum carbon dioxide reduction and energy conservation, and provide reference for route planning decision.