Cooperative task planning for ship and UAVs based on particle swarm optimization algorithm

作者：Ma, Hua-Wei; Zhu, Yi-Min; Hu, Xiao-Xuan

来源：Systems Engineering and Electronics, 2016, 38(7): 1583-1588.

DOI：10.3969/j.issn.1001-506X.2016.07.16

• Adaptive particle swarm optimizations
• Combat capability
• Cooperative tasks
• Inertia weight
• Local optima
• Particle swarm optimization algorithm
• Self-adaptive
• Task planning

Cooperative task planning for ship and unmanned aerial vehicles (UAVs) (CPSU) is a new technology which can make full use of the complementary advantages between ship and UAVs to make task planning cooperatively. It is a new focus on the UAVs'task planning problem, and it has great influence on improving the navy combat capability. A mathematical model of CPSU is built, and then a self-adaptive particle swarm optimization (APSO) algorithm is introduced to solve it. The algorithm can self-adaptively change the inertia weight, which can avoid the PSO trapping into the local optimum better. The experiment shows that the APSO algorithm solves the problem more effectively than the standard PSO and the PSO with the constrict factor.

• 出版日期2016-7-1
• 单位合肥工业大学