摘要
研究飞行器航路规划问题时,由于目标函数复杂,计算量大,采用蚁群算法,存在航路搜索速度慢,容易陷入局部最优从而得不到最优航路的问题,把蚁群算法嵌入到文化算法中,提出了一种文化蚁群算法来解决航路规划问题。计算模型包括蚁群算法的群体空间和利用群体空间最优解的信仰空间。群体空间的群体演化采用蚁群系统,并加入了奖惩机制。信仰空间由群体空间中的最好个体组成,并利用遗传算法的思想进行更新,以指导群体空间的进化。仿真结果表明,提出的算法拥有更快的搜索速度,得到的航路也更好。
The paper proposed a culture ant algorithm by inserting ant algorithm into a computational framework of culture algorithm to solve route planning. The computational framework contains group space based on ant culture al- gorithm and belief space based on the optimal solution of group space. The evolution of group space using ant system and rewards and punishments mechanism was added. The belief space was constructed with the best individual of group space and updated through genetic algorithm in order to guide the evolution of group space. Simulation results show that the speed of this algorithm is faster and the route is better.
出处
《计算机仿真》
CSCD
北大核心
2013年第5期99-103,共5页
Computer Simulation
关键词
飞行器
航路规划
蚁群算法
文化算法
Aircraft
Route planning
Ant algorithm
Culture algorithm
