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Ant colony system based on receding horizon control for aircraft arrival sequencing and scheduling

Published:08 July 2009Publication History

ABSTRACT

The aircraft arrival sequencing and scheduling (ASS) problem is one of the most significant problems in the air traffic control (ATC). This paper makes the first attempt to design an ant colony system (ACS) based approach to solve this NP-hard problem. In order to reduce the computational effort of the optimization process, the receding horizon control (RHC) strategy is integrated into the ACS to divide the optimization process into several sub-processes and solve them one by one. This strategy can reduce the problem scale in each sub-optimization process, resulting in lighter computational effort and higher quality solution for the whole problem. Experiments are conducted to demonstrate the effectiveness and efficiency of the proposed RHC based ACS algorithm for the ASS problem (RHC-ACS-ASS). Simulation results show that the RHC-ACS-ASS not only outperforms the GA based approaches, but also the ACS based approach without using the RHC strategy.

References

  1. X. B. Hu and W. H. Chen, "Genetic algorithm based on receding horizon control for arrival sequencing and scheduling," Eng. Appl. Artif. Intell., vol. 18, no. 5, pp. 633--642, Aug. 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. X. B. Hu and E. D. Paolo, "Binary-representation-based genetic algorithm for aircraft arrival sequencing and scheduling," IEEE Trans. Intell. Transp. Syst., vol. 9, no. 2, pp. 301--310, Jun. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. M. Dorigo and L. M. Gambardella, "Ant colony system: a cooperative learning approach to the traveling salesman problem," IEEE Trans. Evol. Comput., vol. 1, no. 1, pp. 53--66, Apr. 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
      July 2009
      2036 pages
      ISBN:9781605583259
      DOI:10.1145/1569901

      Copyright © 2009 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 8 July 2009

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