Akinori Murata

Optimization of Aircraft Landing Route and Order: An approach of Hierarchical Evolutionary Computation

This paper focuses on the aircraft landing optimization problem where both the landing routes and the landing order of aircrafts should be optimized to minimize an occupancy time of airport , and proposes its optimization method which is robust to dynamical situations such as weather condition change and other aircrafts’ landing routes change. As a difficulty of this optimization problem, appropriate landing routes of aircrafts change depending on such an environment change. To tackle this problem, this paper proposes the hierarchical evolutionary computation to solve the aircraft landing optimization problem. Specifically, our method firstly generates candidates of main landing route of all aircrafts with their own additional sub-routes, which can be applied into the main routes depending on the current environmental situation. Secondly, our method evolves the good combination of landing routes (including their sub-routes) of all aircrafts to minimize an occupancy time of airport. Through the intensive experiment on a benchmark problem, the following implications have been found: (1) our method successfully generates robust landing routes including some sub-routes，which are flexible depending on environmental situations; and (2) Our method can finds an adequate landing order which contributes to reducing the occupancy time.

Towards Adaptive Aircraft Landing Order with Aircraft Routes Partially Fixed by Air Traffic Controllers as Human Intervention

This paper focuses on how cognitive loads of air traffic controllers can be reduced when optimizing both aircraft route and landing order in the airport landing problem (ALP), and proposes its method which can adaptively change the optimized aircraft landing order according to the aircraft routes partially fixed by air traffic controllers as human intervention. Though the intensive simulation on Haneda Airport in ALP, the following implications have been revealed: (1) our proposed optimization method succeeded to mostly maintain the same level of the results without fixing some of aircraft routes (i.e., the mostly same total distance of all aircrafts from the start position to the destination airport) even if air traffic controllers fixed some of aircraft routes; and (2) this result indicates that our proposed method has a great potential of reducing the cognitive loads of air traffic controllers by reducing the number of aircrafts that should be watched with fixing some of aircraft routes.

Optimization of Aircraft Landing Route and Order Based on Novelty Search

This paper focuses on the Aircraft Landing Problem (ALP) and proposes the efficient aircraft landing route and order optimization method compared to the conventional method. As a difficulty in solving ALP, both landing route and order of all aircrafts should be optimized together, meaning that they cannot be optimized independently. To tackle this problem, our method employs novelty search to generate variety candidates of aircraft landing routes, which are indispensable to generate the feasible landing order of all aircraft. Through the experiment on a benchmark problem, it has revealed that the proposed method can reduce the occupancy time of aircrafts in an airport.