Multi-objective Ant Colony Optimization for Weather Avoidance in a Free Flight Environment

Free flight air traffic management is a paradigm shift to move the decision making process for route choices from air traffic controllers to the cockpit. It provides a unique opportunity to optimize flight routes in the presence of hazardous weather. However, the process of maximizing airspace capacity requires robust and safe weather avoidance algorithms. The problem involves a number of potentially conflicting objectives such as optimizing fuel usage and customer comfort. We propose weather avoidance multi-objective heuristics using Ant Colony Optimization (ACO) and A*. We examined two different pheromone update mechanisms; one using a dynamic weighted sum of three objective functions and the other using the concept of strength. Results show that ACO with pheromone updates based on the former method gives better set of non dominated solutions than the latter method and A*.