ALGA在岸基导弹航路规划中的应用研究

摘要

针对基本遗传算法(GA)易局部收敛的缺陷,设计了基于模式搜索的自学习算子,提出一种基于模式搜索的自学习遗传算法(ALGA).通过仿真测试函数将ALGA与基本遗传算法、自适应遗传算法(AGA)进行比较,显示改进的ALGA提高了算法的综合搜索能力.将改进的ALGA运用到岸基导弹航路规划中,并进行仿真实验,仿真结果验证了改进算法的有效性.%The Genetic Algorithm(GA) has the shortcoming of easy to get into local convergence. To solve the problem, we designed a self-learning operator based on pattern search, and proposed an improved Genetic algorithm, Active Learning Genetic Algorithm (ALGA) with pattern search. Simulation test was made to compare ALGA with standard GA and Adaptive Genetic algorithm ( AGA), and the result showed that ALGA can enhance the general search ability. The ALGA was used in the shore-based missiles path planning and validated by simulation.