Exact and Heuristic Methods for Planning and Scheduling Collaborative Manufacturing Systems

Emerging challenges in the manufacturing industry, such as supply chain disruptions, political instability, and difficulty in accessing skilled workforce necessitate a more pragmatic approach to survive in this highly intertwined ecosystem. These approaches aim to empower manufacturing companies’ efficiency and agility while providing a certain degree of resilience. Hence, collaboration among stakeholders by sharing manufacturing resources and information is vital. However, despite the advancements in digital platforms for collaborative manufacturing, there is a need for effective planning of shared resources which is computationally intractable. Approaching this challenging problem from a multi-agent perspective brings new opportunities for modeling and solving. In a collaborative manufacturing network, as a multi-agent system, each manufacturing stakeholder, or agent, can pursue their objective, such as minimizing production time, reducing costs, or improving product quality while a coordinator agent monitors and ensures a solution that is best for all agents. This paper proposes systematic and heuristic methods for planning and scheduling collaborative manufacturing resources using a multi-agent modeling paradigm. The efficiency of the developed methods is benchmarked with randomly generated instances that show promising results for the manufacturing industry.