Application of Genetic Algorithm for Preliminary Trajectory Optimization 2011-01-2594

The aviation sector has played a significant role in shaping the world into what it is today. The rapid growth of global economies and the corresponding sharp rise in the number of people now wanting to travel on business and for pleasure, has largely been responsible for the development of this industry. With a predicted rise in Revenue Passenger Kilometers (RPK) by over 150% in the next 20 years, the industry will correspondingly be a significant contributor to environmental emissions.

Under such circumstances optimizing aircraft trajectories for lowered emissions will play a critical role amongst various other measures, in mitigating the probable environmental effects of increased air traffic. Aircraft trajectory optimization using evolutionary algorithms is a novel field and preliminary studies have indicated that a reduction in emissions is possible when set as objectives. The paper describes a preliminary study undertaken for the Systems for Green Operation Integrated Technology Demonstrator for the Clean Sky Project (FP7) and uses a customized algorithm NSGAMO2 (a proposed variation of the Non-dominated Sorted Genetic Algorithm II). The paper describes the concept of the algorithm, benchmarking studies undertaken to establish its validity, followed by simple trajectory optimization cases optimized for various multi-disciplinary objectives. Results highlighting the tradeoffs between mission fuel burn, mission time and mission NO_x production for a typical short-, medium- and long-range single-aisle narrow-body aircraft are presented.