CAJ | 학술논문

针对多无人作战飞机(UCAV)协同目标分配问题,提出了一种基于混合离散粒子群算法的多UCAV协同目标分配方法.混合离散粒子群算法根据多UCAV协同目标分配问题的特点,设计了新的粒子群位置和速度更新公式,并且充分利用粒子群优化算法的全局搜索能力,同时利用禁忌搜索的局部搜索能力,使2种算法的优势得到互补,较为显著地提升了原算法的性能.仿真结果表明:混合离散粒子群算法能够有效地解决多约束条件下多UCAV协同目标分配问题,并且算法简单、灵活,易于实现和扩展.
침대다무인작전비궤(UCAV)협동목표분배문제,제출료일충기우혼합리산입자군산법적다UCAV협동목표분배방법.혼합리산입자군산법근거다UCAV협동목표분배문제적특점,설계료신적입자군위치화속도경신공식,병차충분이용입자군우화산법적전국수색능력,동시이용금기수색적국부수색능력,사2충산법적우세득도호보,교위현저지제승료원산법적성능.방진결과표명:혼합리산입자군산법능구유효지해결다약속조건하다UCAV협동목표분배문제,병차산법간단、령활,역우실현화확전.
A hybrid discrete particle swarm optimization (HDPSO) algorithm was put forward for multi-UCAV cooperation mission assignment problem. In the algorithm, a new update strategy for the position and speed of particle was applied so as to make the HDPSO algorithm more suitable for multi-UCAV cooperation mission assignment problem. Aiming at the shortcoming of premature and poor resulted from pure PSO, the algorithm performance was enhanced observably by taking full advantage of the global search of particle swarm optimization and the local search of the tabu search algorithm. The simulated results show that the HDPSO algorithm can solve multi-UCAV cooperation mission assignment effectively, which is simple, flexible, easy to implement and expand.