Airline Passenger Planes Arrival and Departure Plan Synchronization and Optimization Using Genetic Algorithms

Although aviation has been hit hard by the pandemic in the last years, air transport is expected to continue to increase, even if some companies go into crisis. Although some companies went bankrupt during the pandemic, new companies were established, and the planes in the bankrupt companies started to fly in other airlines. The number of employees in the aviation industry is also increasing. Road, maritime, and rail transport cannot keep up with the increase in air transport. By 2037, the annual passenger capacity will be predicted to exceed 8 billion or even 9 billion. There are unique airline connections between more than 20 thousand city-pairs worldwide. Despite this, many passengers fly via transit as there are no direct flights from many cities to many cities or because direct flights are sometimes not economical or common. Since, naturally, passengers do not like to wait in transfers, passengers are lost to other flights and airline companies if the airline does not have a suitable flight at the appropriate time for the transfer. Therefore, synchronization and optimization of international and domestic flights are important at major hub airports and major airlines. In this study, we will try to solve this problem by using the genetic algorithm to maximize the number of total passengers for Istanbul Airport, an important global hub airport. The genetic algorithm is a search heuristic that was inspired by Charles Darwin’s theory of natural evolution. This algorithm reflects the process of natural selection, where the fittest individuals are selected for reproduction to produce offspring of the next generation.