A real-time schedule method for aircraft landing scheduling problem based on cellular automaton

  • Authors:

  • Shengpeng Yu;Xianbin Cao;Maobin Hu;Wenbo Du;Jun Zhang

  • Affiliations:

  • Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China;School of Engineering Science, University of Science and Technology of China, Hefei, China;Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China;School of Electronic and Information Engineering, Beihang University, Beijing, China

  • Venue:
  • Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
  • Year:
  • 2009

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Abstract

The Aircraft Landing Scheduling (ALS) problem is a typical hard multi-constraint optimization problem. In real applications, it is not most important to find the best solution but to provide a feasible landing schedule in an acceptable time. We propose a novel approach which can effectively solve the ALS while satisfying the real-time need. It consists of two steps: (i) Use CA to simulate the landing process in the terminal airspace and to find a considerably good landing sequence; (ii) a simple Genetic Algorithm associated with a Relaxation Operator is used to obtain a better result based on the CA result. Experiments have shown that our method is much faster and suitable for real-time ALS problem compared with traditional optimization methods. For all the 13 data sets, the proposed approach can find satisfactory solutions in less than 2 seconds.