Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/90694
Title: Coordinating quality, time, and carbon emissions in perishable food production : a new technology integrating GERT and the Bayesian approach
Authors: Wang, H
Zhan, SL
Ng, CT 
Cheng, TCE 
Issue Date: Jul-2020
Source: International journal of production economics, July 2020, v. 225, 107570
Abstract: 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.
Keywords: Bayesian approach
Food quality
Graphic evaluation and review technique
Multi-objective optimization
Sustainability
Publisher: Elsevier
Journal: International journal of production economics 
ISSN: 0925-5273
DOI: 10.1016/j.ijpe.2019.107570
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