Abstract
Air Traffic Flow Network Rerouting Problem (ATFNRP), which aims to alleviate the flight delays caused by the increasing traffic and extreme weather, has become more and more serious in air traffic flow management. This paper proposes a multi-objective general rerouting model considering both total delay cost and airlines fairness and adopts Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) for ATNFRP. Empirical studies using the real data of China airspace demonstrate that MOEA/D outperforms or performs similarly to three well-acknowledged Multi-Objective Evolutionary Algorithms (MOEAs) on ATFNRP.
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Zhang, X., Xiao, M., Zhang, M. (2013). Multi-Objective Evolutionary Algorithm Based on Decomposition for Air Traffic Flow Network Rerouting Problem. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2013. IDEAL 2013. Lecture Notes in Computer Science, vol 8206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41278-3_59
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DOI: https://doi.org/10.1007/978-3-642-41278-3_59
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