Impacts of sharing production information on supply chain dynamics

Information sharing and coordination between buyers and vendors have been considered as useful strategies to improve supply chain performance. Some researches, however, have reported that not all players in a supply chain are benefited under such strategies. Therefore, the debate is not about whether or not production information should be shared in the supply chain, but about what information to share and how to share most cost-effectively to maximize the mutual benefits of the supply chain as a whole and the individual business players. In this paper a multi-agent simulation model is developed to investigate the issue. The multiagent model supports more comprehensive and flexible modeling capability than traditional modeling approach. Several experiments are designed and conducted to investigate the impacts of different levels of inter-agent cooperation and information sharing between supply chain partners on various performance indicators

[1]  Xiande Zhao,et al.  Forecasting errors and the value of information sharing in a supply chain , 2002 .

[2]  Steven Orla Kimbrough,et al.  Computers play the Beer Game: can artifical agents manage supply chains , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[3]  Stephen F. Smith,et al.  Blackboard Agents for Mixed-Initiative Management of Integrated Process-Planning/Production-Scheduling Solutions Across the Supply Chain , 1997, AAAI/IAAI.

[4]  O KimbroughSteven,et al.  Computers play the beer game , 2002 .

[5]  D. Sterman,et al.  Misperceptions of Feedback in a Dynamic Decision Making Experiment , 1989 .

[6]  Christopher S. Tang,et al.  The Value of Information Sharing in a Two-Level Supply Chain , 2000 .

[7]  Mark S. Fox,et al.  Agent-Oriented Supply-Chain Management , 2000 .

[8]  Jayashankar M. Swaminathan,et al.  Modeling Supply Chain Dynamics: A Multiagent Approach , 1998 .

[9]  Lazaros G. Papageorgiou,et al.  A combined optimization and agent-based approach to supply chain modelling and performance assessment , 2001 .

[10]  David W. Hildum,et al.  MASCOT: An Agent-based Architecture for Coordinated Mixed-Initiative Supply Chain Planning and Scheduling , 1999 .

[11]  X. Wang,et al.  Agent-based information flow for process industries' supply chain modelling , 2000 .

[12]  H. Van Dyke Parunak,et al.  DASCh: Dynamic Analysis of Supply Chains , 1999 .

[13]  George Q. Huang,et al.  Web‐based simulation portal for investigating impacts of sharing production information on supply chain dynamics from the perspective of inventory allocation , 2002 .

[14]  Teruaki Ito,et al.  A blackboard-based negotiation for collaborative supply chain system , 2000 .

[15]  D. Simchi-Levi Designing And Managing The Supply Chain , 2007 .

[16]  Michael J. Shaw,et al.  A multi-agent framework for the coordination and integration of information systems , 1998 .