摘要
针对飞机装配序列规划效率较低的现状,提出一种分阶段模糊遗传算法。对进化过程进行分段,设计一种改进的分段比例选择策略。将模糊算法引入到遗传算法中,通过模糊控制器对遗传算法各个阶段的交叉变异概率进行模糊控制,并根据不同进化阶段的特点设计不同的模糊推理规则和选择压力。算法不仅基于阶段,同时基于个体,提高了收敛速度的同时抑制了早熟现象,保证算法能以较大的概率收敛于全局最优解,大大提高了装配规划效率。以某飞机机翼为例,验证了算法的有效性。
A multi-phase fuzzy genetic algorithm is proposed to improve the efficiency of assembly sequence planning optimization in aircraft assembly.Evolution process is divided into three phases,and an improved proportional selection strategy is designed.Fuzzy algorithm is imported into the genetic algorithm to adjust the crossover and mutation rates during each stage by means of a fuzzy controller,and according to the characteristics of different stages,different fuzzy control rules and selection pressure are designed.The improved algorithm is not only on the basis of evolution stages,but also on individuals,thus improving the convergence speed and restraining the premature convergence and the search has higher possibility of obtaining global optimal solution.Finally,a case of a specific aircraft wing is studied to prove that this method can perform quite well in practical application.
出处
《机械科学与技术》
CSCD
北大核心
2010年第12期1658-1662,共5页
Mechanical Science and Technology for Aerospace Engineering
关键词
装配序列规划
分阶段模糊遗传算法
模糊控制
早熟
assembly sequence planning
multi-phase fuzzy genetic algorithm （MFGA）
fuzzy control
premature convergence
