Coordinating quality, time, and carbon emissions in perishable food production: A new technology integrating GERT and the Bayesian approach

被引:17
作者
Wang, Haiyan [1 ]
Zhan, Sha-lei [1 ]
Ng, Chi To [2 ]
Cheng, T. C. E. [2 ]
机构
[1] Zhejiang Gongshang Univ, Sch Management & EBusiness, Hangzhou 310018, Peoples R China
[2] Hong Kong Polytech Univ, Logist Res Ctr, Dept Logist & Maritime Studies, Hung Hom,Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Sustainability; Food quality; Graphic evaluation and review technique; Bayesian approach; Multi-objective optimization; SUPPLY CHAIN MANAGEMENT; EXPIRATION DATES; NETWORK DESIGN; SHELF-LIFE; SAFETY; MODEL; OPTIMIZATION; LOGISTICS; DECISIONS; TRACEABILITY;
D O I
10.1016/j.ijpe.2019.107570
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页数:18
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