A Multi-Objective Dynamically Optimized Fleet Algorithm for Misty Fields Exploration

The Fleet algorithm is a new meta-heuristic swarm intelligence algorithm inspired by the behavior of fleet exploring unknown regions, collecting and distributing geo-data and deciding on global voyage data acquisition in the Age of Discovery. To address the problem of solving the optimal path for multi-objective path planning in the exploration of the misty aread, this paper proposes and constructs a dynamic path planning model for a fleet of ships exploring global route geo-data. The global optimal path can be effectively planned by fitting the algorithm model description with the historical archival data for deduction.