Coordinating quality, time, and carbon emissions in perishable food production: A new technology integrating GERT and the Bayesian approach
Coordinating quality, time, and carbon emissions in perishable food production: A new technology integrating GERT and the Bayesian approach
复制标题
协调易腐食品生产中的质量、时间和碳排放：集成 GERT 和贝叶斯方法的新技术
DOI：
10.1016/j.ijpe.2019.107570
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发表时间：
2020-07
影响因子：
12
通讯作者：
Cheng T. C. E.
中科院分区：
文献类型：
--
作者：
Wang Haiyan;Zhan Sha-lei;Ng Chi To;Cheng T. C. E.
本研究从管理与技术的联合角度探讨如何提高易腐食品的生产绩效。本文提出了易腐食品可持续质量管理的新思路，近年来引起了越来越多的关注。质量改进活动应在可持续发展的框架内进行。这促使我们在优化QIA决策时，探索涉及易腐食品生产质量、时间和碳排放的三个可持续指标之间的权衡。我们的主要贡献是提出了一种结合图形评估与评审技术（GERT）和贝叶斯方法的新技术，其中GERT可以呈现三个指标的不确定性并预测其预期趋势，贝叶斯方法可以评估三个指标在QIA决策中导致的概率变化。据我们所知，本研究首次将上述决策技术应用于食品质量管理。在此基础上，建立了多目标优化模型，并采用自定义多目标粒子群算法生成三维Pareto前沿以辅助决策。本文以瓶装奶生产为例，对国内某著名乳制品生产企业进行了案例分析。数值结果和管理见解显示了我们技术的优势，其中包括：(1)我们可以减轻不确定性，但不改变粮食生产的随机性；(2)通过增加qia试验规模可以增强三个指标概率变化的稳定性；(3)我们可以从不同的角度可视化三个指标之间的最优权衡；(4)提出了面向节点和面向目标的个性化可持续质量管理方案。总之，我们希望本研究能够在技术创新方面为易腐食品质量管理领域提供有益的补充。
This study concerns improving the performance of perishable food production from the joint perspective of management and technology. We consider a new idea about sustainable quality management for perishable food, which has aroused growing concern recently. Quality improvement activities (QIAs) should be carried out within the framework of the sustainable development. This motivates us to explore the tradeoffs among three sustainable metrics which involve quality, time and carbon emissions in perishable food production when optimizing QIA decision making. Our main contribution is proposing a new technology integrating Graphic Evaluation and Review Technique (GERT) and Bayesian approach, in which GERT can present the uncertainty of the three metrics and forecast their expected trends, and Bayesian approach can evaluate the probabilistic changes of the three metrics resulting from QIA decision making. To the best of our knowledge, this study is the first to use the above decision-making technology in food quality management. Furthermore, a multi-objective optimization model is built and a customized multi-objective particle swarm optimization is employed to generate the three-dimensional Pareto front to aid the decision making. We take bottled milk production as an example and present a case study on a famous Chinese dairy manufacturing firm. Numerical results and managerial insights show the advantages of our technology which include: (1) we can mitigate uncertainty, but do not change the random nature of food production; (2) we can reinforce the stability of the probabilistic change of the three metrics by increasing of the QIA-trial size; (3) we can visualize the optimal tradeoffs among the three metrics from different angles of view; and (4) we can figure out individualized sustainable quality management plans which are node-oriented and objective-oriented. In conclusion, we hope this study can be a beneficial supplement to the quality management field of perishable food with respect to technology innovation.
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DOI：
10.1002/047172212x
发表时间：
2004-04
期刊：
--
影响因子：
--
作者：
W. M. Bolstad
通讯作者：
W. M. Bolstad
影响因子：
12
作者：
Bryndis Stefansdottir;Verena Depping;M. Grunow;U. Kulozik
通讯作者：
Bryndis Stefansdottir;Verena Depping;M. Grunow;U. Kulozik
影响因子：
12
作者：
Mehmet Soysal;J. Bloemhof-Ruwaard;J. Vorst
通讯作者：
Mehmet Soysal;J. Bloemhof-Ruwaard;J. Vorst
影响因子：
12
作者：
F. Sgarbossa;I. Russo
通讯作者：
F. Sgarbossa;I. Russo
DOI：
10.1007/3-540-27659-9
发表时间：
2005-05
期刊：
--
影响因子：
--
作者：
Matthias Ehrgott
通讯作者：
Matthias Ehrgott