汽车混流装配线的混合布谷鸟算法排序研究

Research of mixed-model automobile assembly sequencing based on hybrid cuckoo search algorithm

为解决汽车混流装配线作业者工作负荷不均衡的问题,构建了最小化违背装配频率上限次数的优化模型,提出了布谷鸟算法与遗传算法相结合的混合算法。该方法将遗传算法的选择与交叉思想引入布谷鸟算法的迭代过程,以克服布谷鸟算法寻优过程中收敛速度慢和容易陷入局部最优的问题。测试函数的对比求解和合作汽车企业的优化实例表明该改进算法具有更高的求解精度和更快的收敛速度,能有效地解决大规模的汽车混流装配线排序优化问题。

For the solution of the unbalance workload in mixed-model automobile assembly line,an optimization model,in which the limit of violating assemble frequency is minimized,is constructed and a hybrid method based on cuckoo search algorithm and genetic algorithm is proposed.In the proposed method,by integrating the selection and crossover theory of genetic algorithm into the iteration process of cuckoo search,the problem of cuckoo search algorithm,where the convergence rate has been slowed down and local optimal is easily resulted,is avoided.The results of standard test functions and an application example of cooperation automobile verify that the proposed hybrid method has higher accuracy and faster convergence rate.Therefore,the proposed hybrid method can effectively solve the problem of sequencing optimization in large-scale automobile assembly.