面向混流生产线排序问题的改进回溯搜索算法

Improved Backtracking Search Algorithm Oriented the Problem of Mixed Flow Production Line Sequencing

针对产品工艺的复杂性和多样性导致的混流生产线生产效率低下的问题,建立各个工作站零件利用率最大化和总体均衡化的函数模型,提出了一种基于改进多个目标回溯搜索算法的混流生产线排序方法,利用多权重下的最优个体精英历史种群引导当前种群进化,以提高全部搜索能力的收敛速度。将该算法应用于装配线排序问题上,为混流生产车间的作业排序提供有效的依据;同时将多目标回溯搜索算法与遗传算法、回溯搜索算法进行对比,结果表明改进的回溯搜索算法在混流生产线排序问题上的优越性。

In view of the inefficiency of mixed-flow production line caused by the complexity and diversity of product process,a function model of maximizing the utilization of parts and equalization of the total was established,and a sorting method of mixed-flow production line based on the improvement of multi-objective back-search algorithm was proposed to guide the evolution of the current population by using the optimal individual elite historical population under multiple weights to improve the global search ability and convergence speed of the algorithm.Applying the algorithm to the scheduling of the assembly line provides a basis for sorting the work in the mixed-flow production workshop.At the same time,the multi-objective backtracking search algorithm was compared with genetic algorithm and backtracking search algorithm.The results show that the improved backtracking search algorithm is effective and superior in solving the scheduling problem of mixed-flow production line.