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- W4225525903 abstract "As satellites grow both in number and in the fields involved, it has become an enormous challenge to allocate limited satellite resources against complicated constraints and confined working hours. In this paper, particle swarm optimization integrated with tabu search is introduced to solve the satellite-imaging task-planning issue. Based on the related constraints and construction of a satellite-imaging task-planning model, local search and tabu rules are added to the particle swarm algorithm to improve diversity and effective search. The works of this paper includes but not limited to developing task plans that feature quick convergence and global near-optimal solutions, designing groups of data containing different task loads, comparing the plans in terms of integrated assessment value, the number of tasks completed, task priority, and planning time consumed. The result of the experiment indicate that particle swarm optimization with Tabu search is effective in handling satellite imaging task planning." @default.
- W4225525903 created "2022-05-05" @default.
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- W4225525903 date "2021-12-01" @default.
- W4225525903 modified "2023-10-18" @default.
- W4225525903 title "Satellite Imaging Task Planning using Particle Swarm Optimization and Tabu Search" @default.
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- W4225525903 doi "https://doi.org/10.1109/qrs-c55045.2021.00090" @default.
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