Sustainable Operation and Management of a Dynamic Supply Chain under the Framework of a Community with a Shared Future for Mankind

The values of a community with a shared future for mankind include the views of common interests, sustainable development, and global governance. This article will fully consider introducing the value concept of a community with a shared future into the operation and management of dynamic supply chains. Based on the optimal information fusion mechanism of artificial intelligence, this article aims to examine the operation and management of dynamic supply chains within the framework of a community with a shared future for mankind. The core idea is to consider the common interests among enterprises, establish a global collaborative operation concept for upstream, midstream, and downstream enterprises, and achieve the goal of sustainable development. Firstly, a type of composite dynamic supply chain model is considered, in which the total inventory of each node in the supply chain is further subdivided into raw material inventory and finished product inventory. At the same time, we have considered factors such as the signing of procurement contracts between core enterprises and upstream enterprises, as well as the signing of supply contracts between core enterprises and downstream enterprises. Secondly, the static and dynamic monitoring information of the enterprise has been established. We use steady-state Kalman filtering theory to obtain dynamic reference signals for upstream enterprises, core enterprises, and downstream enterprises. Based on the optimal information fusion processing mechanism of artificial intelligence, the coefficient weighting method is used to obtain the optimal fusion signals of upstream enterprises, core enterprises, and downstream enterprises. Once again, through high-quality switching strategies, enterprises can achieve in-order switching, improve production efficiency, reduce downtime, enhance their competitiveness and responsiveness, and transform the dynamic supply chain, including order switching, into a discrete-time linear switching system for processing. Fourthly, sufficient conditions, robustness analysis results, and inventory control criteria for the solvability of dynamic supply chain H∞ with order switching are provided. Finally, data analysis is conducted using historical order information from three fruit companies to verify the validity and feasibility of the conclusions in this article and to improve the performance of the dynamic supply chain system. The research findings of this article enrich the exploration of the operation and management of dynamic supply chains and the construction of a community with a shared future for mankind.

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Publication Details

Journal
Sustainability
Published
2024-09-06
DOI
https://doi.org/10.3390/su16177780
Citations
4
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
2.22
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article

Sustainable Operation and Management of a Dynamic Supply Chain under the Framework of a Community with a Shared Future for Mankind

Lihua Hu, Tao Fan, Chengjiu Wang
4 citations
Sustainability
Supply Chain Resilience and Risk Management
2.22
article

Sustainable Operation and Management of a Dynamic Supply Chain under the Framework of a Community with a Shared Future for Mankind

Lihua Hu, Tao Fan, Chengjiu Wang
article en
4 citations

Abstract

The values of a community with a shared future for mankind include the views of common interests, sustainable development, and global governance. This article will fully consider introducing the value concept of a community with a shared future into the operation and management of dynamic supply chains. Based on the optimal information fusion mechanism of artificial intelligence, this article aims to examine the operation and management of dynamic supply chains within the framework of a community with a shared future for mankind. The core idea is to consider the common interests among enterprises, establish a global collaborative operation concept for upstream, midstream, and downstream enterprises, and achieve the goal of sustainable development. Firstly, a type of composite dynamic supply chain model is considered, in which the total inventory of each node in the supply chain is further subdivided into raw material inventory and finished product inventory. At the same time, we have considered factors such as the signing of procurement contracts between core enterprises and upstream enterprises, as well as the signing of supply contracts between core enterprises and downstream enterprises. Secondly, the static and dynamic monitoring information of the enterprise has been established. We use steady-state Kalman filtering theory to obtain dynamic reference signals for upstream enterprises, core enterprises, and downstream enterprises. Based on the optimal information fusion processing mechanism of artificial intelligence, the coefficient weighting method is used to obtain the optimal fusion signals of upstream enterprises, core enterprises, and downstream enterprises. Once again, through high-quality switching strategies, enterprises can achieve in-order switching, improve production efficiency, reduce downtime, enhance their competitiveness and responsiveness, and transform the dynamic supply chain, including order switching, into a discrete-time linear switching system for processing. Fourthly, sufficient conditions, robustness analysis results, and inventory control criteria for the solvability of dynamic supply chain H∞ with order switching are provided. Finally, data analysis is conducted using historical order information from three fruit companies to verify the validity and feasibility of the conclusions in this article and to improve the performance of the dynamic supply chain system. The research findings of this article enrich the exploration of the operation and management of dynamic supply chains and the construction of a community with a shared future for mankind.

SustainabilityVol. 16(17)
Guangxi University (CN), Sichuan University of Science and Engineering (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Supply Chain Resilience and Risk Management
2.22
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