sas 16(6): e5

Research Article

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

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  • @ARTICLE{10.4108/eai.3-12-2015.2262953,
        author={Akinori Murata and Masaya Nakata and Hiroyuki Sato and Tim Kovacs and Keiki Takadama},
        title={Optimization of Aircraft Landing Route and Order:        An approach of Hierarchical Evolutionary Computation},
        journal={EAI Endorsed Transactions on Self-Adaptive Systems},
        volume={2},
        number={6},
        publisher={ACM},
        journal_a={SAS},
        year={2016},
        month={5},
        keywords={aircraft scheduling, evolutionary computation, landing path planning},
        doi={10.4108/eai.3-12-2015.2262953}
    }
    
  • Akinori Murata
    Masaya Nakata
    Hiroyuki Sato
    Tim Kovacs
    Keiki Takadama
    Year: 2016
    Optimization of Aircraft Landing Route and Order: An approach of Hierarchical Evolutionary Computation
    SAS
    EAI
    DOI: 10.4108/eai.3-12-2015.2262953
Akinori Murata,*, Masaya Nakata1, Hiroyuki Sato1, Tim Kovacs2, Keiki Takadama1
  • 1: The University of Electro-Communications
  • 2: The University of Bristol
*Contact email: kouho.aki@gmail.com

Abstract

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.