基于改进量子进化算法的巡航导弹航路规划方法

针对巡航导弹作战区域广阔、航路规划效率低的问题，提出了基于改进量子进化算法(IQEA)的巡航导弹航路规划方法。首先分析并确定巡航导弹航路规划空间，建立航路评价的代价指标；针对实数编码量子进化算法容易早熟、陷入局部最优的缺点，引入染色体的概率表达特性，使得每条染色体均能以一定概率表达优化问题的所有可行解；借鉴遗传算法的思想，在IQEA中引入染色体繁殖机制，结合动态量子门实现染色体的进化，实现算法局部搜索和全局搜索的平衡。仿真实验结果表明，基于带繁殖机制的IQEA的航路规划算法能够快速、稳定地搜索到代价更低的航路，所规划航路能够有效进行威胁规避、地形回避和地形跟随。

Cruise Missile Path Planning Based on Improved Quantum Evolutionary Algorithm

For the low efficiency of cruise missile path planning, a novel path planning algorithm is proposed based on improved quantum evolutionary algorithm (IQEA). The search space is constructed based on path constraints, and the criteria of path estimation are presented. Probabilistic representation quantum chromosome is introduced to represent all the feasible solutions probabilistically to solve the premature problem. The genetic algorithm is used for reference, and the breeding strategy is introduced to IQEA. The dynamic quantum rotation gate is used to update the chromosomes to realize a good balance between local and global searches . Simulation results show that IQEA with breeding strategy can generate flight path with lower cost rapidly and steadily.