关键词: 基于移动机器人的拣货系统, 自动拣货系统, 动态货位指派优化, 货到人, 电商

Abstract: Considering the problem of shelves location reassignment of Robotic Mobile Fulfillment System (RMFS)under dynamic demand,the dynamic storage reassignment policy based on matching rate between shelf and location was proposed,and mixed integer programming model which reflected the continuous dynamic variation of warehouse layout was built with the objective of maximizing the correlation between shelves demand frequency and distance to picking station.Single-t Exchange Simulated Annealing(SA-STE)algorithm was designed to solve the dynamic shelves reassignment problems.The results showed that SA-STE algorithm could find the solution close to optimal solution found by CPLEX solver in a relatively short period of time,and its advantages were obvious in large-scale problem.Compared with the traditional random and dedicated assignment strategy,the proposed methods could optimize RMFS by matching shelves location with Stock Keeping Units(SKU) demand pattern dynamically,which was save about 30% traveling distance and improve the operation efficiency of RMFS.

Key words: robotic mobile fulfillment system, automatic picking system, dynamic storage location reassignment optimization, part-to-picker, online retail