The role of pig size prediction in supply chain planning

被引：14
作者：
Apichottanakul, Arthit [2 ]
Pathumnakul, Supachai [2 ]
Piewthongngam, Kullapapruk [1 ]
机构：
[1] Khon Kaen Univ, Fac Management Sci, E Saan Ctr Business & Econ Res, Khon Kaen 40002, Thailand
[2] Khon Kaen Univ, Fac Engn, Supply Chain & Logist Syst Res Unit, Khon Kaen 40002, Thailand
来源：
BIOSYSTEMS ENGINEERING | 2012年 / 113卷 / 03期
关键词：
ARTIFICIAL NEURAL-NETWORK; GROWTH; PARAMETERS; MODEL;
D O I：
10.1016/j.biosystemseng.2012.07.008
中图分类号：
S2 [农业工程];
学科分类号：
0828 ;
摘要：
The pork processing industry struggles with ineffective procurement plans due to the complexities of pig growth estimation. In this study, artificial neural network (ANN) models were applied to estimate the pig size distribution and average weight of pigs in a herd. The results indicated that the developed models provide reasonable prediction solutions with a mean absolute error (MAE) lower than 5.0 and a root-mean square error (RMSE) lower than 7.0 for pig size distribution estimation. The estimates of the average weight of finishing pigs exhibited a MAE of 2.33 and an RMSE of 3.15. Moreover, pig size distribution was applied to the problem of determining a pig procurement plan. Using the proposed concept, a proper procurement plan for each herd can be determined by improving the precision of pig size measurements. Because of its simplicity, this concept is highly applicable to the pork processing industry and offers a potentially large cost reduction. (C) 2012 IAgrE. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：298 / 307
页数：10
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