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Application of Genetic Algorithm for Preliminary Trajectory Optimization
Abstract:
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 NOx production for a typical short-, medium-
and long-range single-aisle narrow-body aircraft are presented.