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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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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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.
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
Sebastian Henn,Algorithms for on-line order batching in an order picking warehouse [J]. Computer & Operations Research, 2012, 2549-2563.
Sebastian Henn,Soren Koch,Karl F.Doerner,ect. Metaheuristics for the Order Batching Problem in the Manual Order Picking System[J]. BuR-Business Research, 2010, Vol.3 (1), pp.82-105
Seval Ene,Nursel Ozturk,Storage location assignment and order picking optimization in the automotive industry[J]. Int J Adv Manuf Technol, 2011, pp.787-797
Osman Kulak,Yusuf Sahin,Mustafa Egemen Taner.Joint order batching and picker routing in single and multiple-cross-aisle warehouse using cluster-based tabu search algorithms[J].Flex Serv Manuf J,2012,(24):52-80
Amir Hossein Azadnia, Shahrooz Taheri, Pezhman Ghadimi, ect. Order Batching in Warehouse by Minimizing Total Tardiness:A Hybrid Approach of Weighted Association Rule Mining and Genetic Algorithms[J].The Scientific World Journal,2013,1-13
Gibson D R,Sharp G.P. Orderbatching Proeedures[J].EuroPean Journal of Operational Researeh, 2005, 58(l), 57-67.
Le-Due, De Koste. Travel distance estimation and storage zone optimization in a 2-bloek class-based storage strategy warehouse [J]. Intemational Joumal of Production Researeh, 2004, 43(17), 3561-3581.
Tho Le-Duc. Design and Control of Efficient Order Picking Processes [M]. Rotterdam:Erasmus University Rotterdam, 2005.
Roodbergen , K.J. and DeKoster,R Routing order Pickers in awarehouse with a middle Aisle[J]. EuroPean Journal of Operational Researeh. 2001, 133, 32-43.
Pratik J Parikh, Russell D Meller. Selecting between batch and zone order picking trategies in a distribution center [J]. Transportation Research Part E, 2008, 44: 696-719.
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