Applying Multi-Agent Negotiation to Solve the Production Routing Problem With Privacy Preserving
It addresses integrated production, inventory, distribution, and routing challenges for supply chain industries, but appears incremental as it combines existing MAS and optimization methods.
This paper tackles the Production Routing Problem with Privacy Preserving in supply chain optimization by proposing a hybrid Multi-Agent System with optimization algorithms, demonstrating effectiveness in real-world applications.
This paper presents a novel approach to address the Production Routing Problem with Privacy Preserving (PRPPP) in supply chain optimization. The integrated optimization of production, inventory, distribution, and routing decisions in real-world industry applications poses several challenges, including increased complexity, discrepancies between planning and execution, and constraints on information sharing. To mitigate these challenges, this paper proposes the use of intelligent agent negotiation within a hybrid Multi-Agent System (MAS) integrated with optimization algorithms. The MAS facilitates communication and coordination among entities, encapsulates private information, and enables negotiation. This, along with optimization algorithms, makes it a compelling framework for establishing optimal solutions. The approach is supported by real-world applications and synergies between MAS and optimization methods, demonstrating its effectiveness in addressing complex supply chain optimization problems.