Abstract
A simultanenous optimization of planning among multi-companies has been widely required from the viewpoint of supply chain management. In a practical situation, a near optimal plan for supply chain planning of the multi-companies should be created by the negotiation and/or 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 an augmented Lagrangian decomposition and coordination method. The proposed method can derive a feasible solution without using the procedure of heuristic generation of feasibile 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 peformance index even though only the local information is used to derive a solution for each company.
