Distributed supply chain planning system for several companies using a new augmented Lagrangian relaxation

Coordination of planning among several companies has been widely received much attention from the viewpoint of global supply chain management. In a practical situations, a plausible plan for several companies should be created by the negotiation and coordination among the companies without sharing the confidential information such as inventory costs, set up costs and due date penalties for each company. In this paper, we propose a framework of a distributed optimization of supply chain planning using a new augmented Lagrangian relaxation method. The feature of the proposed method is that a feasible solution can be derived without using the procedure of heuristic generation of feasible solutions. From the computational experiments, it has been shown that the average gap between the solution derived by the proposed method and an optimal solution is within 1% of the performance index even though only the local information is used to derive a solution for each company.