An Efficient GEP-based Hyper-heuristic Approach for Automatic Airport Gate Assignment Problem

The Airport Gate Assignment Problem (AGAP) is a key optimization problem in air transportation. Heuristic methods are often used to solve AGAP. However, existing heuristic methods have drawbacks such as lack of generality, and inability to adjust dynamically in real-time. To address these issues, this paper proposes a hyper-heuristic framework for AGAP. A hyper-heuristic algorithm (GBHH) is further developed based on the framework and Gene Expression Programming (GEP). Improvements are made to the encoding and decoding processes of GEP to enhance the search performance. Experimental results show that the hyper-heuristic algorithm proposed in this paper performs satisfactorily compared to genetic algorithm (GA), simulated annealing algorithm (SA) and hybrid algorithm (HSATS), especially in terms of search efficiency.

• Publication year

  2023

• Venue

  2023 International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC)

• Publication date

  2023-10-20

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/CSIS-IAC60628.2023.10364183
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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