A scheduling method based on a hybrid genetic particle swarm algorithm for multifunction phased array radar

• Published in: Frontiers of information technology & electronic engineering Vol. 18; no. 11; pp. 1806 - 1816
• Main Authors: Zhang, Hao-wei, Xie, Jun-wei, Lu, Wen-long, Sheng, Chuan, Zong, Bin-feng
• Format: Journal Article
• Language: English
• Published: Hangzhou Zhejiang University Press 01.11.2017; Springer Nature B.V
• Subjects: Chaos theory; Communications Engineering; Computer Hardware; Computer Science; Computer Systems Organization and Communication Networks; Doppler effect; Electrical Engineering; Electronics and Microelectronics; Genetic algorithms; Heuristic; Instrumentation; Mutation; Networks; Phased arrays; Radar; Radar arrays; Schedules; Scheduling; Space surveillance; Task scheduling; Scheduling; Phased array radar; Particle swarm algorithm; TP391; Genetic algorithm; Pulse interleave
• ISSN: 2095-9184; 2095-9230
• DOI: 10.1631/FITEE.1601358

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.