D etermination of the Aircraft Landing Sequence by Two Meta-Heuristic Algorithms

Due to an anticipated increase in air traffic during the next decade, air traffic control in busyairports is one of the main challenges confronting the controllers in the near future. since the runwayis often a bottleneck in an airport system, there is a great interest in optimizing the use of therunway. the most important factors in aircraft landing modeling are time and cost. for this reason,aircraft landing scheduling problem (aslp) is a typical hard multi-constraint optimizationproblem and finding its efficient solution would be very difficult. so in real applications findingthe best solution is not the most important issue and providing a feasible landing schedule in anacceptable time would be the preferred requirement. in this study a three objectives formulation ofthe problem proposed as a mathematical programming model on a runway in static mode. problemis solved by multi-objective genetic algorithm (nsga-ii) and multi-objective particle swarmoptimization algorithm (mopso). considering a group of 20 aircrafts, this problem is solved andlanding sequence determined and we are shown the obtained sequence does not follow first comefirst serve law for sequencing as well. finally by comparing results, conclusion and suggestionsare proposed.