Abstract: Warehousing costs account for a large proportion of the total cost of modern logistics. Reasonably slotting optimization is the core of improving the efficiency of warehouse picking and reducing costs. By analyzing the outbound process of low-level manual picking warehouses and considering in-fluencing factors such as the degree of product hot-selling, the relationship between the products, and the location of shelf, a slotting optimization algorithm based on the community division algorithm is designed. The algorithm firstly builds undirected weighted networks based on the product relevance, and then uses a community division algorithm to divide it multiple times; Secondly, it is stored on the shelf in the community as a unit, and the shelf is filled through the adjustment phase. Finally the optimal product placement is selected from multiple placements based on evaluation indicators. The evaluation index is established based on the three optimization goals of shortening the walking path, alleviating congestion and reducing the number of pickers. Experiments show that the proposed slotting optimization algorithm has significant advantages compared with other comparative solutions in terms of time consumption and the quality of the product placement.

Key words: low-level manual picking warehouse, slotting optimization, community division algorithm, slotting optimization algorithm, evaluation indicator