Multi-objective optimization for multi-satellite scheduling task

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Heba Abdulrahman Khojah
Mohamed Atef Mosa

Abstract

The satellites scheduling mission play an effective role in enhancing the role of ground station control and monitoring systems. In this search, SGSEO is re-formulated into a multi-objective optimization task. Therefore, the Gravitational Search Algorithm GSA is exploited to attain several essential objectives for generating tight scheduling. Moreover, particle swarm optimization model PSO is consolidated with GSA in a novel form for strengthening its ability of local search and slow the speed of convergence. On the other side, to make the most of the satellite resources in the right direction, we have observed targets that have fewer observational opportunities to keep them from being lost. The PageRank algorithm is used to fulfil this issue by ranking the candidate's strips. Finally, the effect of different parameters of the proposed approach was studied by experimental outcomes and compared with previous methods. It has shown that the performance of the proposed approach is superior to its peers from other methods.

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[1]
H. A. Khojah and M. A. Mosa, “Multi-objective optimization for multi-satellite scheduling task”, J. Soft Comput. Explor., vol. 3, no. 1, pp. 19-30, Mar. 2022.
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