An Efficient GEP-based Hyper-heuristic Approach for Automatic Airport Gate Assignment Problem
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- @InProceedings{Wu:2023:CSIS-IAC,
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author = "Jiankai Wu and Shichang Xie and Junlan Dong and
Jinghui Zhong",
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booktitle = "2023 International Annual Conference on Complex
Systems and Intelligent Science (CSIS-IAC)",
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title = "An Efficient {GEP-based} Hyper-heuristic Approach for
Automatic Airport Gate Assignment Problem",
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year = "2023",
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pages = "345--350",
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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.",
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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)",
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DOI = "doi:10.1109/CSIS-IAC60628.2023.10364183",
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month = oct,
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notes = "Also known as \cite{10364183}",
- }
Genetic Programming entries for
Jiankai Wu
Shichang Xie
Junlan Dong
Jinghui Zhong
Citations