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

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@InProceedings{Wu:2023:CSIS-IAC,

• author = "Jiankai Wu and Shichang Xie and Junlan Dong and Jinghui Zhong",
• booktitle = "2023 International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC)",
• title = "An Efficient {GEP-based} Hyper-heuristic Approach for Automatic Airport Gate Assignment Problem",
• year = "2023",
• pages = "345--350",
• abstract = "The Airport Gate Assignment Problem (AGAP) is a key optimisation 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.",
• keywords = "genetic algorithms, genetic programming, Gene expression programming, Heuristic algorithms, Metaheuristics, Simulated annealing, Logic gates, Airports, Search problems, Airport gate assignment problem (AGAP), Hyper-heuristic framework, Scheduling rules(SRs)",
• DOI = "doi:10.1109/CSIS-IAC60628.2023.10364183",
• month = oct,
• notes = "Also known as \cite{10364183}",

}

Genetic Programming entries for Jiankai Wu Shichang Xie Junlan Dong Jinghui Zhong

Citations