@inproceedings{ed131846876744a4b87004c4fea894ef,
title = "Solving airport gate assignment problem using an improved genetic algorithm with dynamic topology",
abstract = "The rapid growth of air transportation demand led to numerous studies on the airport gate assignment problem (AGAP). As the problem scale gets larger, mathematical programming is no longer available, and heuristic methods like genetic algorithm (GA) have been applied. Taking into account of adding soft constraint to the model and ameliorate objective value of the AGAP, this paper proposes an improved GA considering structural properties to avoid GA{\textquoteright}s prematurity. A dynamic topology integrated in crossover operator contributes to a better tradeoff between convergence speed and quality of solutions. Finally, experimental results illustrate the effectiveness of the proposed improved GA to solve AGAP in comparison with traditional GA and a reliable commercial software CPLEX CP Optimizer.",
keywords = "Airport gate assignment problem, Combinatorial optimization, Complex network, Dynamic topology, Genetic algorithm",
author = "Ran Xu and Kaiquan Cai",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2019.; International Conference on Intelligent Computing, Communication and Devices, ICCD 2017 ; Conference date: 09-12-2017 Through 10-12-2017",
year = "2019",
doi = "10.1007/978-981-10-8944-2\_102",
language = "英语",
isbn = "9789811089435",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "877--884",
editor = "Srikanta Patnaik and Vipul Jain",
booktitle = "Recent Developments in Intelligent Computing, Communication and Devices - Proceedings of ICCD 2017",
address = "德国",
}