The enhancement of solving the distributed constraint satisfaction problem for cooperative supply chains using multi-agent systems

Facing global and dynamic competition, companies need to coordinate with supply chain partners to effectively fulfill customer orders. Considering the risk of exposing trade secrets and the cost of gathering information, the centralized constraint optimization mechanism is infeasible when it comes to handling distributed scheduling problems in a real-world environment. This paper proposes an agent-based distributed coordination mechanism that integrates negotiation techniques with genetic algorithm to plan quasi-optimal order fulfillment schedules to meet customers' demands. In this study, to evaluate the performance and feasibility of our proposed mechanism, experiments are conducted using a mold manufacturing supply chain as an example. The experimental results reveal that the proposed distributed coordination mechanism is a feasible approach to resolving the order fulfillment conflicts in a supply chain.