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A Novel Genetic Algorithm with Population Perturbation and Elimination for Multi-satellite TT&C Scheduling Problem

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Bio-inspired Computing: Theories and Applications (BIC-TA 2019)

Abstract

Multi-Satellite Tracking Telemetry and Command Scheduling Problem is a multi-constrained, high-conflict complex combinatorial optimization problem. How to effectively utilize existing resources has always been an important topic in the satellite field. To solve this problem, this paper abstracts and simplifies the Multi-Satellite TT&C Scheduling problem and establishes the corresponding mathematical model. The hybrid goal of maximizing the profit and task completion rate is our objective function. Since the genetic algorithm has a significant effect in solving the problem of resource allocation, we have proposed an improved genetic algorithm with population perturbation and elimination (GA-PS) based on the characteristics of the Multi-Satellite TT&C Scheduling problem. A series of simulation experiments were carried out with the total profits and the task completion rate as the index of the algorithm. The experiment shows that compared with the other three comparison algorithms, our algorithm has better performance in both profit and task completion rate.

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Acknowledgement

This work was supported by the National Natural Science Foundation of China under Grants 71901213, 61473301 and 71690233.

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Correspondence to Ming Chen or Jun Wen .

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Chen, M., Wen, J., Pi, BJ., Wang, H., Song, YJ., Xing, LN. (2020). A Novel Genetic Algorithm with Population Perturbation and Elimination for Multi-satellite TT&C Scheduling Problem. In: Pan, L., Liang, J., Qu, B. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2019. Communications in Computer and Information Science, vol 1159. Springer, Singapore. https://doi.org/10.1007/978-981-15-3425-6_44

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  • DOI: https://doi.org/10.1007/978-981-15-3425-6_44

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3424-9

  • Online ISBN: 978-981-15-3425-6

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