Research On Goods Assignment Problem Based On Serial Partition Pick Pattern

With the rapid development of today's logistics industry,which plays a crucial role in improving the efficiency of the entire logistics system.As one of the core links of logistics distribution center,the efficiency of picking operation has become the key factor which affects the efficient operation of distribution center.At present,the demand of customers gradually presents a trend of multiple varieties,small batch,short response time and big difference,which puts forward higher requirements for the efficiency of picking operation in the distribution center.Therefore,under some certain scenarios,some distribution companies take the example by the manufacturing assembly line production mode and adopt the method of serial partition picking.However,in this way,it causes each of selection station not balanced during the selection process,which further causes the delay between the selection line stations.Therefore,in order to solve this problem,this paper proposes a research method to balance the workload of each picking station and make the picking line run smoothly.First of all,this paper combined with relevant theories at home and abroad,analyzed the serial partition picking mode,found out a decisive factor affecting the picking efficiency,which named unbalanced operation problem between the partitions,and then obtained the characteristics of customer orders through EIQ analysis.Second,according to the two scenarios of serial partition picking mode,the goods distribution problem is divided into the goods distribution problem without considering the picking walk time and the goods distribution problem considering the picking walk time,and then build mathematical models respectively.Genetic algorithm and heuristic algorithm are used to solve the model without considering the walking time,and genetic algorithm is used to solve the model which considering the walking time.Finally,according to the matlab simulation results,we compared and analyzed the changes of each index before and after the model optimization,which proved that the optimization model and algorithm have significant effects on balancing the workload of each picking station and improving the picking operation efficiency.