Joint duration-cost-quality optimization model for complex product supply chains under contingency conditions.

• 出版年: PLoS ONE
• 主要な著者: Yunzhe Li, Peng Dong, Weimin Ye
• フォーマット: 論文
• 言語: 英語
• 出版事項: Public Library of Science (PLoS) 2023-01-01
• オンライン･アクセス: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0292010&type=printable

The Graphical Evaluation and Review Technique (GERT) and complex networks are used to simulate and analyse complex product supply chain networks based on the characteristics of complex product supply chain networks. And the traditional GERT is improved by constructing a grey parametric GERT network with restricted output results, taking into account the fact that the duration, product quality and product cost of each supplier in a complex product supply chain are interval values rather than definite values, and that customers have restrictions on the duration, product quality and product cost of the final product. The functional relationship between product quality, product cost and duration is analysed, and two satisfaction functions for duration and cost are constructed in order to quantify the multi-objective requirements of shortening duration, saving product cost and guaranteeing product quality for complex products under emergency situations. Then, a duration-cost-quality model for complex product supply chains in contingency situations is constructed to obtain the better duration, product cost and product quality of each supplier by optimising the indicator parameters in the network. Finally, the scientific validity and effectiveness of the model and method are verified by means of arithmetic example. The results show that the method is able to analyse the optimal duration, product quality and product cost of each supplier, and the main manufacturer can obtain an optimised combination of duration, cost and quality for a complex product supply chain in different contingency situation. To further promote the sustainable and secure development of complex product supply chains, this paper also suggests the integration of data sharing and blockchain technology with complex product supply chains to develop dynamic supply chain feedback management systems.