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Optimizing dynamic supply chain formation in supply mesh using CSET model

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Abstract

A new e-Service model called dynamic supply chain is characterized by their dynamic nature in easily being formed and disbanded with the seamless connectivity provided by e-Marketplace. The new term “supply mesh” was coined to represent this virtual community of companies in which dynamic supply chains, as per project (also known as make-to-order), are formed across different tiers of suppliers. In a supply mesh, a dynamic supply chain can be formed vertically, from the top to the bottom layers, mediating different companies for a project. Companies that are on the same level laterally are usually competitors, and the companies that are linked vertically as supply chains are trading partners. From a global view, the companies that are connected in the supply mesh can be viewed as individual entities that have self-interest. They may compete for survival as well as collaborate with each other for jobs. Given such complex relations the challenge is to find an optimal group of members for a dynamic supply chain in the supply mesh. A multi-agent model called the collaborative single machine earliness/tardiness (CSET) model was recently proposed for the optimal formation of make-to-order supply chains. This paper investigates the possibilities of applying CSET in a supply mesh, and the corresponding allocation schemes are experimentally studied in simulations. One scheme called Cost-driven principle leads to destructive competition while the other one namely Pareto-optimal evolves into a cooperative competition that tries to mutually benefit every participant. The results, based on samples from the U.S. textile industry, show that a cooperative competition scheme is superior in terms of optimal allocation, which obtains maximum satisfaction for all participants.

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References

  • Banker, S. (2005). The global, make-to-order supply chain: Is it time to examine alternative models, ARC insights. Dedham: Allied Drive.

    Google Scholar 

  • Billesbach, T. J. (1991). A study of implementation of just-in-time in the United States. Production and Inventory Management Journal, 32(3), 1–4.

    Google Scholar 

  • Buyya, R., Abramson, D., Giddy, J. (2000). An economy driven resource management architecture for global computational power grids. Proceeding of International Conference on Parallel and Distributed Processing Techniques and Applications.

  • Chavez, A., & Maes, P. (1996). Kasbah. An agent marketplace for buying and selling goods. Proceedings of the First International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology.

  • Cook, R. L., & Rogowski, R. A. (1996). Applying JIT principles to process manufacturing supply chains. Production and Inventory Management, 1st Quarter, 12–17.

  • Davidson, J. D., & Rees-Mogg, W. (1999). The sovereign individual: Mastering the transition to the information age, 380.

  • Fudenberg, D., & Tirole, J. (1983). Game theory, MIT Press, chapter 1, section 2.4.

  • Harland, C. M. (1996). Supply chain management: Relationships, chains and networks. British Journal of Management, 7, 63–80.

    Article  Google Scholar 

  • Hobbs, O. K. (1994). Application of JIT techniques in a discrete batch job shop. Production and Inventory Management, 1st quarter, 43–47.

  • Holsapple, C., Lai, H., & Whinston, A. (1995). Analysis of negotiation support systems: Roots, progress, and needs. The Journal of Computer Information Systems, 35(3), 2–11.

    Google Scholar 

  • Holsapple, C., Lai, H., & Whinston, A. (1997). Implications of negotiation theory for research and development of negotiation support systems. Group Decision and Negotiation, 6(3), 255–274.

    Article  Google Scholar 

  • Holweg, M., & Pil, F. (2004). The second century: Reconnecting customer and value chain through build-to-order. Cambridge, MA and London, UK: The MIT Press.

    Google Scholar 

  • Homburg, C., & Schneeweiss, C. (2000). Negotiations within supply chains. Computational & Mathematical Organization Theory, 6(1), 47–59.

    Article  Google Scholar 

  • Homburg, C., Koschate, N., & Hoyer, W. D. (2006). The role of cognition and affect in the formation of customer satisfaction: A dynamic perspective. Journal of Marketing, 70(3), 21–31.

    Google Scholar 

  • Kim, H. S., Cho, J. H., Choi, H. R., Hong, S., Kang, M. H. (2006). Optimal supply chain formation using agent negotiation in a SET model-based make-to-order. Proceedings of International Conference on Electronic Commerce, 579–583.

  • Koch, R. (2001). The 80/20 principle: The secret of achieving more with less. London: Nicholas Brealey Publishing.

    Google Scholar 

  • Kropotkin, P. (2005). To alter or to abolish, chapter 5: All against all, Darrell Anderson.

  • Lau, H. C., & Zhang, L. (2004). A two-level framework for coalition formation via optimization and agent negotiation. Proceedings of the intelligent Agent Technology, IEEE Computer Society, 441–445.

  • Lau, H. C., Zhang, L., Liu, C. (2005). Solving generalized open constraint optimization problem using two-level multi-agent framework. Proceedings of the IEEE/WIC/ACM international Conference on intelligent Agent Technology (September 19–22, 2005). IEEE Computer Society, 558–564.

  • Li, C., & Li, L. (2012). Collaboration among mobile agents for efficient energy allocation in mobile grid. Information Systems Frontiers, 14(3), 711–723.

    Article  Google Scholar 

  • Li, H., Ahn, D., Hung, P. C. K. (2004). Algorithms for automated negotiations and their applications in information privacy. Proceedings of the IEEE International Conference on E-Commerce Technology, 255–262.

  • Lim, L., & Benbasat, I. (1993). A theoretical perspective of negotiation support systems. Journal of Management Information Systems, 9(3), 27–44.

    Google Scholar 

  • Liu, R., & Kumar, A. (2011). Leveraging information sharing to configure supply chains. Information Systems Frontiers, 13(1), 139–151.

    Article  Google Scholar 

  • Lo, G., & Kersten, G. E. (1999). Negotiation in electronic commerce: Integrating negotiation support and software agent technologies. Proceedings of 5th Annual Canadian Operational Research Society Conference.

  • Monden, Y. (1981). Adaptive Kanban system helps Toyota maintain just-in-time production. Industrial Engineering, 13(5), 29–46.

    Google Scholar 

  • Nam, I. H. (2003). Benefit of supply chain coordination. Seoul Journal of Business, 9(1).

  • Nowell, C. H. (2005). Market competitiveness in the global textile supply chain: Examination of supply chain configurations. MSc Thesis, North Carolina State University.

  • Putten, S., Robu, V., Poutré, H., Jorritsma, A., Gal, M. (2006). Auto-mating supply chain negotiations using autonomous agents: A case study in transportation logistics. Proceeding of International Conference in Autonomous Agents, the International Workshop on Agent Theories, 1506–1513.

  • Rangaswamy, A., & Shell, G. R. (1997). Using computers to realize joint gains in negotiations: Toward an electronic bargaining table. Management Science, 43(8), 1147–1163.

    Article  Google Scholar 

  • Smith, A. (1950). An inquiry into the nature and causes of the wealth of nations. London: Methuen.

    Google Scholar 

  • Temponi, C., & Pandya, S. Y. (1995). Implementation of two JIT elements in small-sized manufacturing firms. Production and Inventory Management Journal, 3rd Quarter, 23–29.

  • Tian, J., Foley, R., Yao, X., Tianfield, H. (2006). An extended contract net mechanism for dynamic supply chain formation and its application in China petroleum supply chain management. Multiagent and Grid Systems, 183–207.

  • Walker, W. (2004). “Supply chain flexibility”. Montgomery Research ASCET 6.

  • Wigand, R. T., & Benjamin, R. I. (1995). Electronic commerce: Effects on electronic markets. Journal of Computer-Mediated Com-Munication, 1(3).

  • Yang, H., Fong, S., Zhuang, Y. (2008). Applying Pareto-optimal and JIT techniques for supply chains. Proceeding of International Conference on Hybrid Intelligent Systems, 308–313.

  • Yang, H., Fong, S., & Zhuang, Y. (2010). CSET automated negotiation model for optimal supply chain formation. World Review of Science, Technology and Sustainable Development (WRSTSD), 7(1/2), 67–78.

    Article  Google Scholar 

  • You, F., & Grossmann, I. E. (2007). Optimal design and operational planning of responsive process supply chains. Process Systems Engineering, Wiley.

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Correspondence to Simon Fong.

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Yang, H., Fong, S. Optimizing dynamic supply chain formation in supply mesh using CSET model. Inf Syst Front 15, 569–588 (2013). https://doi.org/10.1007/s10796-012-9380-y

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