基于遗传算法的空中加油航路规划

通过对空中加油航路规划进行建模,利用遗传算法进行优化计算,解决了关于包括总耗油量和受油机飞行航程在内的航路规划问题.针对模型中的非线性约束条件,引入自适应可变惩罚以及对部分变量采用过滤法,另外在选择、交叉、变异环节采用适应度选择法、启发式交叉法、非一致变异法,充分利用遗传算法的全局优化特性,解决了局部过早收敛等问题.实际算例中,分别针对基于航线和基于区域2种加油模式进行计算,比较2种模式的优缺点,得出了空中加油的最优策略,并验证了针对此类问题遗传优化算法的有效性.

Air Refueling Journey Planning Based on Genetic Algorithm

Based on a model for the schedule of several times air refueling in the journey, the paper analyses and solves the journey programming problem involving the total fuel consumption and the flight distance of the deploying aircraft by the genetic algorithm (GA). By introducing auto-adaptive punishment, initial filtration, normalized geometric ranking, non-uniform mutation,heuristic crossover methods into GA, the problem related to nonlinear restriction and convergence in local area is solved. The practices prove the efficiency of GA and put forward an optimizing solution for the journey programming problem by computing and comparing the results based on the journey-based mode and area-based mode.