基于遗传算法的人工拣选优化研究

为研究人工拣选作业中路径优化问题.在ABC存储策略下的双区域仓储布局中,建立路径模型,利用遗传算法求解最优路径,进行仿真实验,与S型、返回型拣选路径的最优解进行比较.仿真结果表明,在拣选件数较少时,遗传算法有明显的优势,在拣选件数较多时,3种方法趋于相近,且遗传算法的适用性受到仓库布局的影响.经优化后的路径能够节约拣选作业的时间,加快仓储内货物周转的速度,提高整个物流活动的效率,有助于物流活动快速及时地完成,增强客户满意度.

The Optimization Research of Manual Picking Based on Genetic Algorithm

Research on path optimization problem in manual order picking. Under the condition of ABC storage strategy and double regional warehouse layout, path model was set up. Use genetic algorithm to solve the optimal path, make simulation experiments, and compare the optimal solution of S-shape, return-shape picking path models. The simulation results show that when small picking number, the genetic algorithm has obvious advantages, when large picking number, the three methods tend to be more close. And the applicability of the genetic algorithm was affected by the warehouse layout. The optimized picking path saves operation time, speeds up the flow of goods within the warehouse, improves the efficiency of the whole logistics activity, helps logistics activities completed quickly, and enhances customer satisfaction.