基于PSC-IGA算法的数字化车间仓配一体化研究

Research on the integration of warehousing and distribution in digital workshop based on PSC-IGA

文章针对数字化车间内部的仓配一体化问题,以装配生产线的物料需求时间和数量为拉动因素,考虑物料配送效率和立库运行效率,将仓配问题分为2个层次,首先通过生产排程确定时间窗,以配送效率最大化为目标构建物料配送路径规划模型,然后构建货位分配多目标优化模型。采用两阶段的遗传算法进行求解,提出基于多色集合约束的遗传算法(polychromatic sets constraints of improved genetic algorithm,PSC-IGA),在求解第2层时利用第1层的路径结果建立布尔围道矩阵,降低搜索范围。最后针对实际算例得出满足生产需求的仓配一体化方案。研究表明,将车间配送和仓储问题有机融合不仅能提高生产效率,还能提高算法的收敛速度,验证了模型的可行性和算法的优越性。

This paper focuses on the problem of integration of warehousing and distribution in the digital workshop.Taking the material demand time and quantity for the assembly line as the pulling factors,considering the material delivery efficiency and the operating efficiency of the warehouse,the warehousing and distribution problem is divided into two levels:firstly,based on the time window determined by the production schedule,the material delivery path planning model is constructed with the goal of maximizing the distribution efficiency,and then a multi-objective optimization model of cargo space allocation is built.This paper adopts the two-stage genetic algorithm for solving problems,and puts forward the polychromatic sets constraints of improved genetic algorithm(PSC-IGA).When solving the second layer,the path results of the first layer are used to establish Boolean chromatic matrix and lower the searching range.Finally,a warehousing and distribution integration scheme satisfying the production demand is obtained through examples.The research shows that the integration of workshop distribution and warehouse problems not only improves the production efficiency,but also improves the convergence speed of the algorithm,which verifies the feasibility of the model and the superiority of the algorithm.