An Augmented Lagrangian Approach for Decentralized Supply Chain Planning for Multiple Companies

Abstract

Coordination and optimization of supply chain planning among multiple companies have widely been received much attention from viewpoints of global supply chain management. Conventional system for supply chain planning is configured on the assumption that correct information for entire company is available by sharing the detailed information among multiple companies. It is required to generate a near optimal plan for multiple companies without sharing the confidential information such as inventory costs, set up costs and due date penalties among competing companies. In this paper, we propose a framework of a distributed supply chain planning for multiple companies by using an augmented Lagrangian relaxation approach. The proposed method features that a feasible solution can be derived without using the entire information by exchanging the data which is not directly related to cost data. 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.

Dynamic mutual adjustment search for supply chain operations planning co-ordination

“…In order to develop a coordination system that truly respects the distributed nature of supply chain, some authors , Karakitsiu and Migdalas 2008, Nishi et al 2005a propose an asynchronous and decentralized adjustment process of these penalties.…”

“…These approaches then need to restore feasibility of the constraints that still remain violated. In order to develop a coordination system that truly respects the distributed nature of supply chain, some authors , Karakitsiu and Migdalas 2008, Nishi et al 2005a propose an asynchronous and decentralized adjustment process of these penalties. In this approach, there is no need of a central mediator to coordinate the supply chain partners operations planning processes.…”

“…• Hierarchical planning and information sharing techniques The main decomposition approach used in the literature of supply chain planning coordination, with 10 contributions, is Lagrange decomposition , Karakitsiu and Migdalas 2008, Xiao et al 2007, Nishi et al 2005a, Nishi et al 2005b). This approach exploits the block-separability property of such a problem.…”

“…In Lagrange decomposition , Karakitsiu and Migdalas 2008, Xiao et al 2007, Nishi et al 2005a, Nishi et al 2005b) a central block-separable supply chain planning model using mathematical programming is developed. Then the binding constraints of the natural sub-problems, which are typically the material flow constraints between supply chain partners are relaxed (by moving them in the objective function and adding a penalty vector for each constraint).…”