Open AccessMulti-sensor scheduling method based on Cuckoo and Particle Swarm optimization algorithm
Author(s) -
Wei Wei,
Changyun Liu,
Chuang Wang,
LI Jun-xia
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1651/1/012064
Subject(s) - particle swarm optimization , cuckoo search , mathematical optimization , computer science , multi swarm optimization , algorithm , cuckoo , jump , scheduling (production processes) , firefly algorithm , metaheuristic , convergence (economics) , swarm behaviour , mathematics , zoology , physics , quantum mechanics , economics , biology , economic growth
In order to solve the problem that particle swarm optimization (PSO) tends to fall into the local optimal solution and the convergence speed is slow when solving multi-sensor resource scheduling model, a cuckoo particle swarm optimization (CPSO) algorithm is proposed on the basis of PSO. On the basis of target tracking model, the multi-sensor scheduling model is established. Then the LEVY flight was introduced from cuckoo algorithm into particle swarm algorithm, the algorithm can jump out of the local optimal solution as soon as possible and improve the convergence speed and accuracy of the algorithm. The simulation results show that the improved algorithm is effectively improved in terms of convergence speed and accuracy, and is applied to the solution of sensor scheduling model to further enhance the optimization ability and achieve good results.