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Research on Dynamic Scheduling Method of Aerospace TT&C System Based on Chaos Genetic Algorithm

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Frontier Computing on Industrial Applications Volume 2 (FC 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1132))

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Abstract

The research direction is the dynamic scheduling method of aerospace surveying and mapping system based on chaotic genetic algorithm. This is a new technology to solve complex problems in aerospace systems and has been proved to be very effective in solving these problems. The dynamic scheduling algorithm, which can be used as a tool to improve aircraft performance by reducing turnaround time. This will help airlines reduce operating costs and increase profits. This paper aims to design a dynamic scheduling method for aerospace T/C system based on chaotic genetic algorithm. It also includes simulation results and performance analysis of the proposed method in different parameters (such as number of jobs, number of machines, number of processors, etc.).

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References

  1. Jiang, T., Cai, Y., Yan, L., et al.: Research on method of aerospace test resource matching optimization based on improved genetic algorithm. Comput. Measur. Control (2012)

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Author information

Authors and Affiliations

  1. Beijing Institute of Spacecraft Environment Engineering, Beijing, 100029, China

    Xinghua Sun

Authors
  1. Xinghua Sun
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Correspondence to Xinghua Sun .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung City, Taiwan

    Jason C. Hung

  2. School of Computer Science and Engineering, University of Aizu Tsuruga, Aizuwakamatsu, Japan

    Neil Yen

  3. Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung City, Taiwan

    Jia-Wei Chang

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sun, X. (2024). Research on Dynamic Scheduling Method of Aerospace TT&C System Based on Chaos Genetic Algorithm. In: Hung, J.C., Yen, N., Chang, JW. (eds) Frontier Computing on Industrial Applications Volume 2. FC 2023. Lecture Notes in Electrical Engineering, vol 1132. Springer, Singapore. https://doi.org/10.1007/978-981-99-9538-7_48

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  • DOI: https://doi.org/10.1007/978-981-99-9538-7_48

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9537-0

  • Online ISBN: 978-981-99-9538-7

  • eBook Packages: EngineeringEngineering (R0)

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