Title:
Demand-supply alignment in supply chain networks with access to hyperconnected production options
Demand-supply alignment in supply chain networks with access to hyperconnected production options
Author(s)
Pothen, Ashwin
Inan, Mahmut Metin
Montreuil, Benoit
Lauras, Matthieu
Benaben, Frederick
Xie, Yao
Inan, Mahmut Metin
Montreuil, Benoit
Lauras, Matthieu
Benaben, Frederick
Xie, Yao
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Abstract
Supply chain networks today comprise of various decentralized actors, subject to constantly evolving challenges and customer expectations, and operate in a volatile, uncertain, and disruption-prone environment. These challenges and complexities bring in informational and material flow distortions, making it hard to align demand and supply with agility. Building a centralized optimization model for such complex systems tends to be computationally expensive and unscalable for real-world application. With this motivation, we propose a novel, real-world applicable multi-agent-based approach for collaborative and agile demand-supply alignment, through dynamic prediction-driven planning and operational decision-making. We first demonstrate the applicability and configurability of our approach with a real-world supply chain network operating in a stochastic and disruptive environment, with the desired characteristics in congruence with the Physical Internet framework. We then demonstrate the simulation-testing capability of our approach by highlighting the potential benefits of leveraging a hyperconnected network of open certified production options.
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Date Issued
2023-06
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Text
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Paper