Abstract
A hybrid optimization approach combining a particle swarm algorithm, a genetic algorithm, and a heuristic inter-leaving algorithm is proposed for scheduling tasks in the multifunction phased array radar. By optimizing parameters using chaos theory, designing the dynamic inertia weight for the particle swarm algorithm as well as introducing crossover operation and mutation operation of the genetic algorithm, both the efficiency and exploration ability of the hybrid algorithm are improved. Under the frame of the intelligence algorithm, the heuristic interleaving scheduling algorithm is presented to further use the time resource of the task waiting duration. A large-scale simulation demonstrates that the proposed algorithm is more robust and efficient than existing algorithms.
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Project supported by the National Natural Science Foundation of China (Nos. 61503408 and 61601504)
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Zhang, Hw., Xie, Jw., Lu, Wl. et al. A scheduling method based on a hybrid genetic particle swarm algorithm for multifunction phased array radar. Frontiers Inf Technol Electronic Eng 18, 1806–1816 (2017). https://doi.org/10.1631/FITEE.1601358
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DOI: https://doi.org/10.1631/FITEE.1601358