Study on Order Batching Model Design Based on Hopfield Neural Network
Science Journal of Business and Management
Volume 3, Issue 2, April 2015, Pages: 60-64
Received: Apr. 11, 2015; Accepted: Apr. 18, 2015; Published: May 4, 2015
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Authors
Hong Zhang, School of Information, Beijing Wuzi University, Beijing, China
Jie Zhu, School of Information, Beijing Wuzi University, Beijing, China
Li Zhou, School of Information, Beijing Wuzi University, Beijing, China
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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.
Keywords
Manual Order Picking System, Order Batching, Stochastic Service System, Hopfield Neural Network
To cite this article
Hong Zhang, Jie Zhu, Li Zhou, Study on Order Batching Model Design Based on Hopfield Neural Network, Science Journal of Business and Management. Vol. 3, No. 2, 2015, pp. 60-64. doi: 10.11648/j.sjbm.20150302.12
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