引入优化算子的无人机遗传航路规划算法研究

在大范围真实地形环境中规划出满足任务要求、导航、安全性等约束的较优航路,对提高无人机(UAV)的武器系统性能有重要意义。在基于直接航路编码的遗传算法中引入优化操作算子,将复杂约束合理地应用于遗传进化过程,可以较好地克服一般遗传操作的不足。采用均匀设计的试验方法确定较优的控制参数,并通过算例验证了算法的有效性。

Using Local Optimization Operator in Genetic Algorithm for UAV Route Planning Problem

To get the optimal flight routes which satisfy constraints such as mission request, navigation and security in large scope and real terrain important to enhance the unmanned aerial vehicle (UAV)'s weapon system efficiency. An improved genetic algorithm which based on direct encoding method of individual and local optimization operator is represented to solve the route planning problem. By applying the complex constraints to the evolutionary process, the algorithm can overcome the drawbacks of canonical GA. The control parameters are selected by the uniform design of the experimental method, and the result of examples has proved that the algorithm is effective.