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DIGITAL TWIN (DT)-DRIVEN REAL-TIME OPTIMIZATION AND RESILIENCE FRAMEWORK FOR PERISHABLE SUPPLY CHAINS USING MIP AND AGILE QUALITY TOOLS
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DOI：10.17270/J.LOG.001323.png)
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Abstract
En 中文
Background: Perishable supply chains face persistent challenges arising from product perishability, demand fluctuations, and frequent disruptions. Conventional models lack the real-time adaptability required to effectively manage spoilage while maintaining service levels. This paper proposes an integrated decision-support framework that leverages Digital Twin (DT) technology, Mixed-Integer Programming (MIP), and Agile Quality Tools to enhance resilience and quality preservation in perishable supply chains. Methods: The proposed framework integrates DT-enabled real-time monitoring, predictive analytics, and adaptive re-optimization. MIP is employed to support routing and inventory decisions, while Agile Quality Tools, such as Failure Mode and Effects Analysis (FMEA) and control charts, are used to dynamically adjust model parameters in response to freshness deviations and disruption signals. Case studies from food and pharmaceutical supply chains were conducted to evaluate performance under both stable and disrupted operating conditions. Results: The DT-driven framework significantly outperformed baseline models in both domains. In the food supply chain, spoilage was reduced by more than 35%, service levels improved by over 7%, product freshness increased, and total costs declined by nearly 9%. In the pharmaceutical cold chain, spoilage was reduced by over 60%, service levels exceeded 97%, and recovery from disruptions was 37% faster, with costs reduced by about 12%. Across all scenarios, the framework demonstrated high adaptability and operational efficiency, achieving near real-time optimization with an average CPU time of 2.45 seconds. Conclusions: Integrating DT, MIP, and Agile Quality Tools offers a robust, adaptive, and cross-domain solution for perishable supply chains. The proposed framework enhances resilience, minimizes spoilage, reduces operational costs, and ensures higher service levels under uncertainty. Its multidisciplinary nature offers clear value for both academic research and industrial practice.
Keywords:
supply chain network
perishability
digital twin
mixed integer programming
agile quality tools
resilience
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