货位载重约束下自动化仓库货位实时分配技术研究

传统分配方法忽略了货位载重约束，且采用的寻优方法容易陷入局部最优，导致货位分配结果稳定性和出入库效率低、阻塞时间长。为此，提出一种货位载重约束下自动化仓库货位实时分配方法。对货位分配问题进行分析，依据出库时间目标构建货架稳定性模型，对货架稳定性模型进行货位载重、存取和存储约束；引入Pareto最优解，通过遗传方法对目标函数进行求解，求解过程包括染色体编码、染色体解码、适应度函数和种群选择、交叉和遗传。实验结果表明，所提方法稳定性和出入库效率高、缓冲区阻塞时间短。

Location constraints of automated warehouse storage real-time load distribution technology research

The traditional allocation method ignores the section load constraints, and the optimization method is easy to fall into local optimum, leading to stability and storage location assignment results in low efficiency, long time blocking. Therefore, proposed real-time allocation method of automated warehouse storage space under the constraint of a truck. The location allocation problem are analyzed, based on the goal of building a library of time shelf stability model of storage load, access and storage constraints on the shelf stability model. The Pareto optimal solution is introduced, and the objective function is solved by genetic algorithm. The solving process includes chromosome coding, chromosome decoding, fitness function and population selection, crossover and inheritance. The experimental results show that the proposed method has high stability, high efficiency and short buffer time.