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Ant colony algorithm for satellite control resource scheduling problem

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Abstract

With the increasing number of satellite, the satellite control resource scheduling problem (SCRSP) has been main challenge for satellite networks. SCRSP is a constrained and large scale combinatorial problem. More and more researches focus on how to allocate various measurement and control resources effectively to ensure the normal running of the satellites. However, the sparse solution space of SCRSP leads its complexity especially for traditional optimization algorithms. As the validity of ant colony optimization (ACO) has been shown in many combinatorial optimization problems, a simple ant colony optimization algorithm (SACO) to solve SCRSP is presented in this paper. Firstly, we give a general mathematical model of SCRSP. Then, a optimization model, called conflict construction graph, based on visible arc and working period is introduced to reduce workload of dispatchers. To meet the requirements of TT & C network and make the algorithm more practical, we make the parameters of SACO as constant, which include the bounds, update and initialization of pheromone. The effect of parameters on the algorithm performance is studied by experimental method based on SCRSP. Finally, the performance of SACO is compared with other novel ACO algorithms to show the feasibility and effectiveness of improvements.

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Acknowledgements

This work is supported by National Natural Science Foundation of China (NSFC) under Grant 61305149, 61503164, 61573172. The Natural Science Foundation of Jiangsu Provence under Grant BK 20140241.

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Authors and Affiliations

  1. School of Electrical Engineering and Automation, Jiangsu Normal University, Jiangsu, 221116, China

    Zhaojun Zhang & Funian Hu

  2. School of Information and Control Engineering, Xi’an University of Architecture and Technology, Shaanxi, 710055, China

    Na Zhang

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  1. Zhaojun Zhang
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  2. Funian Hu
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  3. Na Zhang
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Correspondence to Zhaojun Zhang.

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Zhang, Z., Hu, F. & Zhang, N. Ant colony algorithm for satellite control resource scheduling problem. Appl Intell 48, 3295–3305 (2018). https://doi.org/10.1007/s10489-018-1144-z

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  • DOI: https://doi.org/10.1007/s10489-018-1144-z

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