Study on Order Batching Model Design Based on Hopfield Neural Network

Abstract

With the rapid development of e-commerce and the global economy, order picking mode of multiple batches and small quantities becoming more and more, which makes artificial picking system occupy a larger proportion in a variety of ways. The optimization study of the artificial person picking system has a crucial role to enhance the efficiency of batch picking, then increasing customer satisfaction. For order batching problem, according to scholars in the study of this problem, including taking the picking equipment capacity and load restrictions into account rarely. In the paper, Hopfield Neural Network algorithm for sorting equipment were chosen to establish a capacity constraint order batching model which taking shortest path of all orders as the objective function and maximum equipment utilization order batching model.