Supply Chain Information Collaborative Simulation Model Integrating Multi-Agent and System Dynamics

  • Ning Yang Qingdao Lanzhi Modern Service Industry Digital Engineering Technology Research Center
  • YingZi Ding Qingdao Lanzhi Modern Service Industry Digital Engineering Technology Research Center
  • Junge Leng Qingdao Lanzhi Modern Service Industry Digital Engineering Technology Research Center
  • Lei Zhang Qingdao Branch, China United Network Communications Co., Ltd.
Keywords: supply chain management, information collaboration, multi-agent, system dynamics, computer simulation

Abstract

Supply chain collaboration management is a system-atic, integrated and agile advanced management mode, which helps to improve the competitiveness of enterprises and the entire supply chain. In order to realise the synergy of supply chain, the most important is to realise the dynam-ic synergy of information. Here we proposed a strategy to integrate system dynamics and multi-agent system model-ling methods. Based on the strategy of supply chain infor-mation sharing and coordination, a two-level aggregation hybrid model was designed and established. Through the computer simulation analysis of the two modes before and after information collaboration, it is found that under the information collaboration mode, the change trend of or-der or inventory of suppliers and manufacturers always closely matches that of retailers. After the implementation of supply chain information coordination, ordering and inventory can be reasonably planned and matched, and problems such as over-stocking or short-term failure to meet order demands caused by poor information commu-nication will no longer occur, which can greatly reduce the “bullwhip effect”.

References

Li ML, Yang H, Guo X. Research on supply chain collaborative manufacturing mode. Journal of Physics Conference Series. 2020;1670(1): 012027. doi: 10.1088/1742-6596/1670/1/012027.

Shan HM, Li Y, Shi J. Influence of supply chain collaborative innovation on sustainable development of supply chain: A Study on Chinese Enterprises. Sustainability. 2020;12(7): 2978. doi: 10.3390/su12072978.

Cannella S, Dominguez R, Framinan JM, Bruccoleri, M. Insights on partial information sharing in supply chain dynamics. 2015 International Conference on Industrial Engineering and Systems Management, 21-23 Oct. 2015, Seville, Spain. 2015. p. 344-350. doi: 10.1109/IESM.2015.7380181.

Wiengarten F, et al. Collaborative supply chain practices and performance: Exploring the key role of information quality. Supply Chain Management. 2010;15(6): 463-73. doi: 10.1108/13598541011080446.

Wu IL, Chuang CH, Hsu CH. Information sharing and collaborative behaviors in enabling supply chain performance: A social exchange perspective. International Journal of Production Economics. 2014;148: 122-132. doi: 10.1016/j.ijpe.2013.09.016.

Yuan HQ, et al. Analysis of coordination mechanism of supply chain management information system from the perspective of block chain. Information Systems and E-Business Management. 2020;18(4): 681-703. doi: 10.1007/s10257-018-0391-1.

Zhang F, Xiao F. Simulation research on information sharing value evaluation of supply chain with multi-agent. In: Wang Q. et al. (eds) 4th Conference on Systems Science, Management Science and System Dynamics, CSS 2010, 10-12 Dec. 2010, Shanghai, China. Beijing: Publishing House Electronics Industry; 2021. p. 99-104.

Abdullah MA, Hishamuddin H. System dynamics approach in supply chain management: A review. In: Haron CHC, et al. (eds) Proceedings of the International Conference on Advanced Processes and Systems in Manufacturing, APSIM 2016, 28-30 Aug. 2016, Kuala Lumpur, Malaysia. 2016. p. 61-62. doi: 10.1109/APSIM.2016.1408893.

Angerhofer BJ, Angelides MC. System dynamics modelling in supply chain management: Research review. In: Joines JA, Barton RR, Kang K, Fishwick PA. (eds) IEEE WSC 2000: Proceedings of the 2000 Winter Simulation Conference, IEEE WSC 2000, 10-13 Dec. 2000, Orlando, FL, USA. New York: IEEE; 2000. p. 342-351. doi:10.1109/WSC.2000.899737.

Dominguez R, Cannella S. Insights on multi-agent systems applications for supply chain management. Sustainability. 2020; 12(5): 1935. doi: 10.3390/su12051935.

Hernandez JE, Poler R, Mula J. Modelling collaborative forecasting in decentralized supply chain networks with a multiagent system. In: Cordeiro J, Filipe J. (eds) 11th International Conference on Enterprise Information Systems - Artificial Intelligence and Decision Support Systems, ICEIS 2009, 6-10 May 2009, Milan, Italy. Setubal: Insticc-Inst Syst Technologies Information Control & Communication; 2009. p. 372-375. doi: 10.5220/0002008503720375.

Hernandez JE, Mula J, Poler R, Lyons AC. Collaborative planning in multi-tier supply chains supported by a negotiation-based mechanism and multi-agent system. Group Decision and Negotiation. 2014;23(2): 235-269. doi: 10.1007/s10726-013-9358-2.

Tian J, Tianfield H. Literature review upon multi-agent supply chain management. 2006 International Conference on Machine Learning and Cybernetics, 8-16 Aug 2006, Dalian, China. New York: IEEE; p. 89-94. doi: 10.1109/icmlc.2006.258877.

Nawarecki E, Kozlak J. Building multi-agent models applied to supply chain management. Control and Cybernetics. 2010;39(1): 149-176. doi: 10.1109/WSC.2000.899737.

Bo SY, Jian DX. Research on management of supply chain based on system dynamic. IEEE ICLSIM 2010 International Conference on Logistics Systems and Intelligent Management, IEEE ICLSIM 2010, 9-10 Jan. 2010, Harbin, China. New York: IEEE; 2010. p. 1329-1332. doi: 10.1109/iclsim.2010.5461180.

Aslam T, Ng AHC. Strategy evaluation using system dynamics and multi-objective optimization for an internal supply chain. In: Yilmaz L, et al. (eds) IEEE WSC 2015: Proceedings of the 2015 Winter Simulation Conference, IEEE WSC 2015, 6-9 Dec. 2015, Huntington Beach, CA, USA. New York: IEEE; 2015. p. 2033-2044. doi: 10.1109/WSC.2015.7408318.

Wikarek J, Sitek P. A multi-level and multi-agent approach to modeling and solving supply chain problems. In: Bajo J, et al. (eds) 14th International Conference on Practical Applications of Agents and Multi-Agent Systems. International Workshops of PAAMS 2016, 1-3 June 2016, Sevilla, Spain. Berlin: Springer-Verlag; 2016. p. 49-60. doi: 10.1007/978-3-319-39387-2_5.

Shu T, et al. Supply chain grounded on information theory: Tracing to the source of collaborative information. 2008 4th IEEE International Conference on Management of Innovation and Technology, IEEE ICMIT 2008, 21-24 Sep. 2008, Bangkok. New York: IEEE; p. 1072-1076. doi: 10.1109/icmit.2008.4654517.

Hernandez JE, Poler R, Mula J, de la Fuente D. Collaborative tactical planning in multi-level supply chains supported by multiagent systems. In: Ortiz A, Franco RD, Gasquet PG. (eds) BASYS: International Conference on Information Technology for Balanced Automation Systems: Proceedings of the Balanced Automation Systems for Future Manufacturing Networks, BASYS 2010, 21-23 July 2010, Valencia, Spain. Berlin: Springer-Verlag; 2010. p. 260-267. doi: 10.1007/s10726-013-9358-2.

Hernandez JE, Mula J, Poler R, Pavon J. A multiagent negotiation based model to support the collaborative supply chain planning process. Studies in Informatics and Control. 2011;20(1): 43-54. doi: 10.24846/v20i1y201104.

Yao YL, Evers PT, Dresner ME. Supply chain integration in vendor-managed inventory. Decision Support Systems. 2007;43(2): 663-674. doi: 10.1016/j.dss.2005.05.021.

Wang JR, Li J, Zhang YH, Hu ZW. Simulation study on influences of information sharing to supply chain inventory system based on multi-agent system. 2008 IEEE International Conference on Automation and Logistics, IEEE ICAL 2008, 1-3 Sep. 2008, Qingdao China. New York: IEEE; 2008. p. 1001-1004. doi: 10.1109/ical.2008.4636297.

Published
2022-09-30
How to Cite
1.
Yang N, Ding Y, Leng J, Zhang L. Supply Chain Information Collaborative Simulation Model Integrating Multi-Agent and System Dynamics. Promet [Internet]. 2022Sep.30 [cited 2022Dec.2];34(5):711-24. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/4092
Section
Articles