遗传帝国竞争混合算法在装配序列规划中的研究与应用

Research and Application of Hybrid Genetic Imperial Competition Algorithms in Assembly Sequence Planning

为了提高复杂产品的装配效率,对遗传帝国竞争混合算法进行了研究与改进,给出了混合算法的融合策略,以解决虚拟装配中的装配序列规划问题。建立考虑装配序列可行性、装配序列稳定性、装配重定向性以及装配聚合性四个评价指标的适应度函数,以适应度函数值最低为目标利用混合算法进行迭代。以某乘用车后桥减速器为实例进行试验,验证了混合算法在求解装配序列规划问题的可行性,并同单一的遗传算法、帝国竞争算法及粒子群算法进行比较,验证了混合算法在求解装配序列规划问题上的优越性。

In order to improve the assembly efficiency of complex products,the hybrid algorithm of genetic and imperial competition algorithm are studied and improved,the fusion strategy of the hybrid algorithm is given to solve the assembly sequence planning problem in virtual assembly. Fitness function of four evaluation indexes including feasibility of assembly sequence,stability of assembly sequence,assembly redirection and assembly aggregation is established.Taking a rear axle reducer of a passenger car as an example,the feasibility of the hybrid algorithm in solving assembly sequence planning problem is verified,and compared with single genetic algorithm,imperial competition algorithm and particle swarm optimization algorithm,the superiority of the hybrid algorithm in solving assembly sequence planning problem is verified.