战术训练空域规划优化仿真研究

Tactical Training Simulation Research on Airspace Planning Optimization

战术训练空域规划是对航空兵战术训练所需空域的集中规划。由于空域的复杂性和训练科目的多样性,人工排样无法保证空域的利用率。针对空域的不规则性,在分析研究BL算法的基础上,提出了基于最低水平线的择优插入算法,考虑周边空域的合理利用。针对空域的有限性,在基本遗传算法的基础上加以改进,编写了选择算子,交叉算子及适应度函数,并将遗传算法与改进后的排样算法结合来进行排样优化。结果表明上述算法能够保证空域的利用率,可为实际中的空域战术训练规划提供科学依据。

Airspace planning of tactical training is a centralized planning, which is typical for Air Force tactical training. Because of the complexity of airspace and the diversity of training courses, artificial packing cannot guarantee the utilization rate of airspace. Due to the irregularities of airspace, the minimum horizon merit - based insertion algorithm is proposed based on analysis of BL algorithm considering the reasonable utilization of surrounding airspace. On account of airspace limitation, the selection operator, the crossover operator and the fitness function are established based on basic genetic algorithm, and for the purpose of packing optimization, genetic algorithm and improved packing algorithm are combined. The results show that the algorithm can ensure the utilization of airspace. The above method may provide a scientific basis for airspace planning of tactical training in real life.