An augmented Lagrangian approach for decentralized supply chain planning for multiple companies

Tatsushi Nishi, Masami Konishi, Ryuichi Shinozaki

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1168-1173
Number of pages6
JournalConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2
Publication statusPublished - 2005
EventIEEE Systems, Man and Cybernetics Society, Proceedings - 2005 International Conference on Systems, Man and Cybernetics - Waikoloa, HI, United States
Duration: Oct 10 2005Oct 12 2005

ASJC Scopus subject areas

  • Engineering(all)

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