基于混合C-W节约与遗传算法的多AMR拣选路径规划优化方法研究

Optimization Method of Multi-AMR Picking Path Planning Based on Hybrid C-W Saving and Genetic Algorithm

针对智能仓库中新型拣选模式下多AMR拣选路径规划问题,给出了一种新的优化模型和改进的混合C-W节约与遗传算法。首先根据作业点对物品的需求顺序、紧急程度进行打分,将物品分流。然后,考虑到AMR数量和作业点暂存位置有限,进行AMR调度和路径规划,以使物品能够及时送达作业点。通过该方法,在满足物品时间窗与AMR配送能力限制的前提下,使完成配送的物品数量最大化。遗传算法中确定了规划方案编码,解决了规划方案的单点交叉问题;引入改进的C-W节约算法,在不破坏原有染色体结构的情况下,不断为群体提供新的优良个体。所建模型及算法是提高了AMR的拣选效率,降低了其运行成本。最后,通过进行比较分析,进一步验证了该算法的有效性与稳定性。

For the multi-AMR picking path planning problem in the intelligent picking mode in smart warehouse,a new optimization method based on hybrid C-W saving and genetic algorithm are proposed.Firstly,the items are scored and triaged according to the order of demand,the urgency at the operation points.Then,constrained by the number of AMRs and the limited number of staging locations at the operation points,AMR scheduling and path planning are performed to enable the items to be delivered to the operation points in time.In this method,the summary score of items is maximized while satisfying the item time window and AMR delivery capacity constraints.The planning scheme coding method is proposed in the genetic algorithm to solve the single-point crossover problem.The improved C-W saving algorithm is introduced to continuously provide new good individuals for the population without destroying the original chromosome structure.The proposed model and algorithm are to improve the picking efficiency of AMR and reduce its operation cost.Finally,the effectiveness and stability of the algorithm in this paper are further verified by conducting comparative analysis.