An adaptive multi-agent system for cost collaborative management in supply chains

• To apply context-aware reasoning to cost collaborative management in supply chains.
• To design a new intelligent system framework of adaptive multi-agent system (AMAS) for CCM.
• To improve the capabilities of coordination and interaction with external context-aware in CCM.

An area that has received much research attention in recent years is the design of self-adaptive multi-agent systems (MAS) for cost collaborative management (CCM) of supply chains. We propose a new system that integrates multi-agents, context-aware computing, and context-aware reasoning to improve CCM in supply chains. The main conclusions of our study indicate that these concepts, methods, and mechanisms such as context-aware computing and context-aware reasoning can be used to create a framework for designing self-adaptive MAS-CCM systems, enhance the coordination and interaction of the system with the external environment, and strengthen the capability of the system for self-learning and self-adaptation. And we use a case study to confirm that environmental uncertainty can be automatically reduced to a win-win mode demonstrating the self-adaptive property of the AMAS-CCM system through a context-aware database, and collaborative capabilities can solve current adaptability and cost control optimization in supply chain members.