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IJAT Vol.10 No.4 pp. 632-638
doi: 10.20965/ijat.2016.p0632
(2016)

Technical Paper:

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Designing Multi-Agent Simulation with Big Time Series Data for a Global Supply Chain System

Kenji Tanaka*, Shen-Ming Gu**, and Jing Zhang**,†

*Department of System Innovation, Graduate School of Engineering, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

**School of Mathematics, Physics and Information Science, Zhejiang Ocean University
No.1, Haida South Road, Lincheng, Changzhi Island, Zhoushan, Zhejiang 316022, P.R. China

†Corresponding author,

Received:
September 19, 2015
Accepted:
May 10, 2016
Published:
July 5, 2016
Creative Commons License
Keywords:
global supply chain, multi-agent simulation, forecast, lead time, inventory
Abstract
Multinational corporations produce products at relatively few factories and then sell those products in all areas of the world. Longer lead times increase the risk of fluctuations in product demand. To reduce this risk, the entire business chain, from production to sale, must be optimized. In this study, we propose, implement, and verify a total optimization system. This system uses multi-agent simulation on big time series data. It consists of management, integrated database, and operation modules.
Cite this article as:
K. Tanaka, S. Gu, and J. Zhang, “Designing Multi-Agent Simulation with Big Time Series Data for a Global Supply Chain System,” Int. J. Automation Technol., Vol.10 No.4, pp. 632-638, 2016.
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