Frequent pattern-based parallel search approach for time-dependent agile earth observation satellite scheduling

Abstract

To address the time-dependent agile earth observation satellite (AEOS) scheduling problem more effectively, the frequent pattern-based parallel search (FPBPS) algorithm is proposed, which is composed of a parallel local search procedure, a competition-based algorithm and operator adaptive selection procedure and the new solutions construction method based on frequent pattern. First, the algorithm and the operator are selected from the algorithm pool and operator pool and run in parallel. As a result, some high-quality and diverse solutions are obtained in a short time. Second, we update the probability of each algorithm and operator to strengthen the self-adaptive ability of the algorithm. Third, frequent pattern mining method is used to extract knowledge with respect to AEOS scheduling to construct new solutions, and parallel local search is applied to further improve these solutions. Finally, extensive experiments prove that the FPBPS algorithm has a better performance than other comparison algorithms in the quality of solution, computation time, and robustness.