| Warehouse management accounts for a high proportion in the logistics cost structure.As the most labor-intensive part in warehouse management,order picking is the key to improve warehouse operation efficiency and reduce storage costs.For a long time,order picking has been a hot research field of logistics theory and application.At present,scholars at home and abroad mainly improve order picking efficiency and reduce warehouse operation cost by optimizing storage location assignment,order batching,and picker routing.For an actual order picking process,however,the storage allocation will affect the order batching mode,and then affect the path planning.Moreover,under the condition that the carrying capacity of a single vehicle is limited,how to batch the order will affect the goods to be picked by the single vehicle,and finally affect the picker route distance.At the same time,in the actual operation process,considering the capacity limitation of carts,inseparable order picking,and order picking efficiency,the total amount of goods in the same order batch is often less than the maximum cart capacity,which leads to the waste of cart capacity and the increase of picking route.Therefore,it has become a problem that cannot be ignored in the actual warehouse management of enterprises to optimize the warehouse order picking based on the order splitting picking strategy in order to improve the order picking efficiency.Based on the research background of online supermarket retail,under the complete split picking strategy of orders and for the improve of order picking efficiency,this paper studies the storage location assignment problem before order arrival and the joint order batching and picker routing problem when order arrives.The SLAP model,which is based on classified storage method and correlation strength,and the JOBPRP model,which is based on the compound scheme of routing and picking quantity,are proposed.At the same time,this paper also proposes a scheme database update strategy to realize the continuous feasibility of the scheme database,and a two-stage heuristic algorithm is designed.The optimization research on three main factors influencing the picking efficiency in warehouse order picking is realized.The main study contents are as follows.Firstly,based on the association strength between goods and the classified storage strategy and taking no storage conflict as constraints,a storage location assignment model is established,and a genetic algorithm is designed to solve the model,obtaining the storage adjustment strategy in line with the current goods demand mode.Second,the third type of data,that is,the historical order picking scheme accumulated by the enterprise in the actual operation process,is used to build the strategy database of route and picking quantity.Then,taking these schemes as decision variables and the goods demand in the actual orders as constraints,the joint optimization model of order batching and path routing is constructed and solved to obtain the implemented scheme and its execution times for completing order picking tasks.At the same time,in order to ensure the sustainable feasibility of the strategy database,a two-stage heuristic algorithm is designed and used to make new schemes of picker routing and picking quantity based on the current order set to update the strategy database.Finally,the effectiveness and feasibility of the method proposed in this paper are proved by comparing with the test results which are recently published in foreign journals.Based on the classified storage strategy and demand correlation strength,the storage location assignment problem under the order splitting picking strategy is discussed and studied.Further,with the routing and picking quantity scheme of carts as decision variables and the actual goods demand as constraints,this paper establishes a new method to make the order picking decision under the separable picking strategy of orders.And the systematic optimization of warehouse order picking problem is realized. |
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