Abstract
As with the rapid development of air transportation and potential uncertainties caused by abnormal weather and other emergencies, such as Covid-19, irregular flights may occur. Under this situation, how to reduce the negative impact on airlines, especially how to rearrange the crew for each aircraft, becomes an important problem. To solve this problem, firstly, we established the model by minimizing the cost of crew recovery with time-space constraints. Secondly, in view of the fact that crew recovery belongs to an NP-hard problem, we proposed an improved particle swarm optimization (PSO) with mutation and crossover mechanisms to avoid prematurity and local optima. Thirdly, we designed an encoding scheme based on the characteristics of the problem. Finally, to verify the effectiveness of the improved PSO, the variant and the original PSO are used for comparison. And the experimental results show that the performance of the improved PSO algorithm is significantly better than the comparison algorithms in the irregular flight recovery problem covered in this paper.
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Acknowledgment
The study was supported in part by the Natural Science Foundation of China Grant No. 62103286, No. 71971143, No. 62001302, in part by Social Science Youth Foundation of Ministry of Education of China under Grant 21YJC630181, in part by Guangdong Basic and Applied Basic Research Foundation under Grant 2021A1515011348, 2019A1515111205, 2019A1515110401, 2020A1515010752, in part by Natural Science Foundation of Guangdong Province under Grant 2020A1515010749, 2020A1515010752, in part by Key Research Foundation of Higher Education of Guangdong Provincial Education Bureau under Grant 2019KZDXM030, in part by Natural Science Foundation of Shenzhen under Grant JCYJ20190808145011259, in part by Shenzhen Science and Technology Program under Grant RCBS20200714114920379, in part by Guangdong Province Innovation Team under Grant 2021WCXTD002.
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Zhou, T., He, P., Zhang, C., Lai, Y., Zhong, H., Wu, X. (2022). An Improved Particle Swarm Optimization Algorithm for Irregular Flight Recovery Problem. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2022. Lecture Notes in Computer Science, vol 13344. Springer, Cham. https://doi.org/10.1007/978-3-031-09677-8_17
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DOI: https://doi.org/10.1007/978-3-031-09677-8_17
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