Volume 2, Issue 3, May 2016, Page: 36-40
Fresh Food Distribution Center Storage Allocation Strategy Analysis Based on Optimized Entry-Item-Quantity-ABC
Zhu Jie, School of Information, Beijing Wuzi University, Beijing, China
Liu Xiaoli, School of Information, Beijing Wuzi University, Beijing, China
Li Juntao, School of Information, Beijing Wuzi University, Beijing, China
Received: Mar. 30, 2016;       Accepted: Apr. 14, 2016;       Published: May 17, 2016
DOI: 10.11648/j.ijdst.20160203.11      View  3485      Downloads  121
Abstract
For labour-intensive field, appropriate storage location assignment is the best choice to increase order picking efficiency and reduce order cycle time, which satisfy customers and reduce cost at the same time. In this paper, we advance a storage location assignment for fresh food distribution center with a manual picker-to-parts picking system by using an optimized approach. To reflect the customer demand uncertainty, the orders received in a certain time range have been grouped and given the different coefficients according to the reference value of them. On that basis, the storage location can be designed optimally based on the Entry-Item-Quantity (EIQ) analysis, which can be used to resolve some orders picking issues, long-picking time and high inventory costs, caused by seasonal change of fresh food, unstable customer demand and repeat purchases. From the computational results, new storage allocation strategy achieves at most a 16% reduction in travel time.
Keywords
Orders Weighting Coefficient, EIQ-ABC, Storage Assignment
To cite this article
Zhu Jie, Liu Xiaoli, Li Juntao, Fresh Food Distribution Center Storage Allocation Strategy Analysis Based on Optimized Entry-Item-Quantity-ABC, International Journal on Data Science and Technology. Vol. 2, No. 3, 2016, pp. 36-40. doi: 10.11648/j.ijdst.20160203.11
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Report on Operation and Investment Strategy of China's Fresh Food E-commerce Industry. (http://www.researchandmarkets.com/research/r3q5s8/report_on)
[2]
Mengnan, W. (2011), Study on Logistics Center Location Optimization Based on Genetic Algorithm, DLMU, Dalian.
[3]
Yinghui, Z. (2015), Study on Optimization of J E-commerce Enterprise Logistics Center, BJTU, Beijing.
[4]
Bryan, J. (2015), “storage policy should not be too cumbersome,” China Logistics & Purchasing, Vol. 15, pp. 64-65.
[5]
Zizheng, D. (2015), “Influence of two kinds of display modes on the storage of freezer by numerical simulation technology,” Food and Machinery, Vol. 3, pp. 145-149.
[6]
Zaerpour, N., Y. Yu, and M. B. M. de Koster. 2011. “Optimal Configuration of a Live-cube Compact Storage System in Service Industries.” Working Paper. Rotterdam: Rotterdam School of Management, Erasmus University
[7]
Yu, Y., and M. B. M. de Koster. 2012. “Class-based Storage with Finite Number of Items.” Working Paper. Rotterdam: Rotterdam School of Management, Erasmus University.
[8]
Yu, Y., and M. B. M. de Koster. 2009. “Optimal Zone Boundaries for Two-class-based Compact Three-dimensional Automated Storage and Retrieval Systems.” IIE Transactions 41 (3): 194–208.
[9]
Bartholdi, J. J., and S. T. Hackman. 2011. Warehouse and Distribution Science: Release 0.95. http://www.warehouse-science.com. Accessed 21 December 2012.
[10]
Hausman, W. H., L. B. Schwarz, and S. C. Graves. 1976. “Optimal Storage Assignment in Automatic Warehousing Systems.” Management Science 22 (6): 629–638.
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