Planning a glider mission in an uncertain environment, with multiple parameters at the same time is a hard 4D (longitude, latitude, depth, time) Multi-Objective Optimization Problem. Multiple approaches are being used to do Glider Path Planning. In this work, we present a new system for helping multi-objective glider path planning in real missions, composed by a path simulator, coupled with the
... [Show full abstract] genetic algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm II), producing a set of multiple Pareto-optimal solutions for the specified objectives: goal distance and trajectory safety