Demand-supply alignment in supply chain networks with access to hyperconnected production options

Overview & Synopsis

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.