Systems Engineering and Electronics ›› 2021, Vol. 43 ›› Issue (1): 171-180.doi: 10.3969/j.issn.1001-506X.2021.01.21

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Multi-satellite scheduling problem based on task merging mechanism

Songlian REN1,2(), Haiquan SUN1,2(), Peng JIN1,2()   

  1. 1. School of Management, Hefei University of Technology, Hefei 230009, China
    2. Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei 230009, China
  • Received:2020-04-10 Online:2020-12-25 Published:2020-12-30

Abstract:

In the traditional pattern, the satellite adopts the single task observation mode, in which the imaging accuracy of the task is high. However, the imaging quantity of the task is small and the utilization rate of the resource is extremely low. Therefore, a multi-task merging mechanism (MTMM) based on the single task observation mode is designed, which adopts the way of task merging in the case of ensuring the minimum imaging requirements of users. Firstly, on the basis of the merging task set, a multi-satellite scheduling model is established, and then an algorithm of improved ant colony optimization based on task merging (IACO-TM) is proposed for the model. In the algorithm, an adaptive ant window strategy, a forced disturbance mechanism and a parameters dynamic adjustment strategy of the algorithm are designed, so as to cut the ant search space effectively, avoid the algorithm falling into the local optimum and improve the convergence speed of the algorithm at the same time. Finally, a large number of simulation experiments are provided to verify the effectiveness of MTMM and IACO-TM, comparing with the algorithm of improved ant colony optimization (IACO) and the algorithm of traditional ant colony optimization based on task merging (TACO-TM).

Key words: multi-satellite scheduling, task merging, ant colony algorithm, self-adaption

CLC Number: 

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