Abstract: The rapid development of e-business (EB for short) requires EB companies to respond to consumer requirements quickly, in order to improve their efficiency of customer services, more and more EB companies have deployed distributed distribution center systems. A main problem with using this system is that improper “goods-warehouse” allocation may result in a large number of orders being divided into multiple sub-orders, which not only causes inconvenience to customers, but also increases more operating costs to companies. Addressing to this problem, we propose a “goods-warehouse” allocation model aimed at minimizing the total number of split orders. Our model is based on a hypergraph representation of historic orders, where each vertex corresponds to a distinct goods appearing in the orders, and each hyperedge describes a co-occurrence relation of goods in a same orders. We first perform spectrum decomposition on the Laplace matrix of the hypergraph to obtain the embedding representations of the goods, then we propose a constrained clustering algorithm and apply it to the above embeddings to generate the allocation results. We conduct comprehensive simulations to evaluate the proposed model, where we use LDA (Latent Dirichlet Allocation) with variant parameter settings to simulate different ordering behaviors, and apply our proposed model as well as some other comparison models to generate the allocation results from the data. All experimental results show the superior of our model.

Key words: “goods-warehouse” allocation, hypergraph, embedding representation, clustering, operations optimization