The Research Of Order Picking Optimization Facing B2C Electronic Business Platform

With the rapid development of B2C E-commerce, a large number of parcels consequent pressure on the process of logistics center. In the "double eleven" period and "double twelve" and other promotional activities, warehouse often occur "warehouse explosion" phenomenon, affecting the user experience. In such a situation, how to improve the efficiency of logistics warehouse, to reduce the "warehouse explosion" phenomenon, it is a problem of logistics enterprises focus, In the operation process in the warehouse, sorting time should be occupied by more than 40 percent of the warehouse job time. Practice has proved that, through the rational allocation of storage and order batching, can not only improve the level of logistics warehouse inventory management, but also help to improve the efficiency and level of logistics center sorting, shortening processing time of sorting link.Research issues of order sorting include warehouse layout, storage allocation, order batching and route optimization these issues, which have a great impact on the efficiency and level of sorting. In this paper, for B2C electronic business platform order picking optimizing, storage allocation and order batching of sorting processes can be optimized to reduce the total travel distance of the sorting process, improve the efficiency of logistics and sorting. Firstly, we build storage allocation model, the first use of association rule algorithm to calculate how often the item in the algorithm, and then consider the goods out of storage frequency and goods value and the distance from the exit to obtain fitness of storage with the goods (C value), based on the value of the more reasonable distribution of storage. To construct orders batching model later, design Canopy and K-Means algorithm order batching algorithm, the same number of channels in the seed algorithm is as the similarity coefficients between the orders, initial clustering is obtained by Canopy algorithm, subsequent use K-Means clustering algorithm to get the results in batches. The paper also compared the effects for the order batching of using random assignment policy and storage allocation policy. Numerical experiments show that by improved the allocation of storage and order batching method can effectively reduce the sorting distance, improve sorting efficiency.