针对标准遗传算法中存在早熟收敛、后期收敛速度慢以及解精度低的问题,结合正交试验设计和元胞自动机模型,提出了一种改进的加速并行遗传算法(APGA)。APGA利用正交试验设计确定较好的初始种群,利用元胞自动机模型固有的并行计算能力设计并行遗传算法,借助元胞信息的动态性和多元性实现正交加速过程。仿真结果表明,APGA能够有效地防止早熟收敛,可以极大地提高遗传算法的搜索效率和解的精度。
In order to resolve the problems of simple genetic algorithm such as premature convergence, low speed of later convergence and its rough result, an orthogonal design and cellular automata based acceleration parallel genetic algorithm (APGA) is presented. Orthogonal design is introduced to generate an initial population that are scattered uniformly over the feasible solution space; The intrinsic capacity of cellular automata is introduced to design parallel genetic algorithm; The dynamic and multiple of cellular information is introduced to achieve orthogonal acceleration process. The simulation results show that APGA can resolve premature convergence effectively and improve the search efficiency and result precision of genetic algorithm greatly.