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Aircraft conflict resolution method based on hybrid ant colony optimization and artificial potential field

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References

  1. Liu W Y, Hwang I. Probabilistic trajectory prediction and conflict detection for air traffic control. J Guid Control Dyn, 2011, 34: 1779–1789

    Article  Google Scholar 

  2. Lü R L, Guan X M, Li X Y, et al. A large-scale flight multi-objective assignment approach based on multiisland parallel evolution algorithm with cooperative coevolutionary. Sci China Inf Sci, 2016, 59: 072201

    Article  Google Scholar 

  3. Tomlin C, Pappas G J, Sastry S. Conflict resolution for air traffic management: a study in multiagent hybrid systems. IEEE Trans Autom Control, 1998, 43: 509–521

    Article  MathSciNet  Google Scholar 

  4. Colorn A, Dorigo M, Maniezzo V. An investigation of some properties of an ant algorithm. In: Proceedings of Parallel Problan Solving from Nature Conference (PPSN 92), Brussels, 1992. 509–520

    Google Scholar 

  5. Guan X M, Zhang X J, Lü R L, et al. A largescale multi-objective flights conflict avoidance approach supporting 4D trajectory operation. Sci China Inf Sci, 2017, 60: 112202

    Article  Google Scholar 

  6. Qian C, Shi J C, Tang K, et al. Constrained monotone k-submodular function maximization using multi-objective evolutionary algorithms with theoretical guarantee. IEEE Trans Evol Comput, 2017. doi: 10.1109/TEVC.2017.2749263

    Google Scholar 

  7. Qian C, Yu Y, Zhou Z H. Pareto ensemble pruning. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI’15), Austin, 2015. 2935–2941

    Google Scholar 

  8. Du W B, Liang B Y, Yan G, et al. Identifying vital edges in Chinese air route network via memetic algorithm. Chinese J Aeronaut, 2017, 30: 330–336

    Article  Google Scholar 

  9. Du W B, Zhou X L, Lordan O, et al. Analysis of the Chinese airline network as multi-layer networks. Transport Res Part E-Log Transport Rev, 2016, 89: 108–116

    Article  Google Scholar 

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. U1533119) and State Key Program of National Natural Science Foundation of China (Grant No. 71731001).

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Authors and Affiliations

  1. School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China

    Huaxian Liu, Feng Liu & Xuejun Zhang

  2. National Key laboratory of Communication, Navigation, Surveillance and Air Traffic Management (CNS/ATM), Beihang University, Beijing, 100191, China

    Huaxian Liu, Feng Liu & Xuejun Zhang

  3. Department of General Aviation, Civil Aviation Management Institute of China, Beijing, 100102, China

    Xiangmin Guan

  4. School of Engineering and Materials Science, Queen Mary University of London, London, E1 4NS, UK

    Jun Chen

  5. Direction des Services de la Navigation Aérienne (DSNA), Reims, 51100, France

    Pascal Savinaud

Authors
  1. Huaxian Liu
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  2. Feng Liu
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  3. Xuejun Zhang
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  4. Xiangmin Guan
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  5. Jun Chen
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  6. Pascal Savinaud
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Corresponding author

Correspondence to Xuejun Zhang.

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Liu, H., Liu, F., Zhang, X. et al. Aircraft conflict resolution method based on hybrid ant colony optimization and artificial potential field. Sci. China Inf. Sci. 61, 129103 (2018). https://doi.org/10.1007/s11432-017-9310-5

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  • DOI: https://doi.org/10.1007/s11432-017-9310-5

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