Análisis de comportamiento caótico en variables de la cadena de suministro

Authors

  • Sergio A. Ramírez Magíster en Sistemas. Universidad EAFIT – Bogotá, Colombia.
  • Gloria E. Peña Universidad Nacional de Colombia, Escuela de Ingeniería de la Organización, Medellín.

DOI:

https://doi.org/10.46631/jefas.2011.v16n31.05

Keywords:

Supply chain management, logistics, Chaos Theory, system dynamics, simulation, Beer Game

Abstract

In this article we develop a supply chain model of four levels through the utilization of system dynamics with Ithink® and Mathlab® softwares to analyze data. The supply chain is studied from the chaos theory perspective, which helps identifying the sensitive variables that can lead to a state of chaos. A generic structure model that comprehends factory links, distribution, wholesale, retail and the client is constructed. The difficulty of operations and logistics managers to decide how much to order and when to do it is simulated accordingly to what occurs in the links of the preceding and subsequent levels with two decision parameters: The first parameter denominated A indicates the participation (between 0 and 1) of the number of product units that are taken into account in the actual stock and the pending orders at the moment of performing an order. The second parameter, denominated B, is the participation (between 0 and 1) of the number of units in the supply line (in transit) at the moment of performing orders of each of the links of the supply chain.

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References

Special Issue: The Dynamics of Supply Chains and Networks. (2005). System Dynamics Review (Vol. 21). Norwich, Great Britain: Wiley.

Akkermans, H., & Dellaert, N. (2005). The Rediscovery of Industrial Dynamics: The Contribution of System Dynamics to Supply Chain Management in a Dynamic and Fragment World. System Dynamics

Review, 21(3), 173-186.

Andersen, D. F., & Sturis, J. (1988). Chaotic Structures in Generic Management Models: Pedagogical Principles and Examples. System Dynamics Review, 4(1-2), 218-245.

Anderson Jr., E., Morrice, D. J., & Lundeen, G. (2005). The “physics” of Capacity and Backlog Management in Service and Custom Manufacturing Supply Chain. System Dynamics review, 217-247.

Chopra, S., & Meindl, P. (2008). Administración de la cadena de suministro. México: Pearson Educación.

Drew, S., Joe, B. H., & Jonathan, R. R. (2006). Enhancing Supply Chain Solutions with the Application of Chaos Theory. Supply Chain Management, 11(2), 108-114.

Forrester, J. W. (1971). Dinamica Industrial. Buenos Aires, Argentina: Ateneo.

Goncalves, P., Hines, J., & Sterman, J. (2005). The Impact of Endogenous Demand on Push-Pull Production Systems. System dynamics review, 187-216.

Hwarng, H. B., & Xie, N. (2008). Understanding Supply Chain Dynamics: A Chaos Perspective. European Journal of Operational Research, 184(3), 1163- 1178.

Larsen, E. R., Morecroft, J. D. W., & Thomsen, J. S. (1999). Complex Behaviour in a Production-Distribution Model. European Journal of Operational Research, 119(1), 61-74.

Mosekilde, E., & Larsen, E. R. (1988). Deterministic Chaos in the Beer Production-Distribution Model. System Dynamics Review, 4(1-2), 131-147.

Paik, S. K., & Bagchi, P. K. (2007). Understanding the Causes of the Bullwhip Effect in a Supply Chain: International Journal of Retail & Distribution Management. Emerald Group Publishing Limited,

(4), 308-322.

Sterman, J. D. (1989). Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment. Management Science, 35(3), 321-339.

Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. New York: Mc Graw Hill

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Published

2011-12-30

How to Cite

Ramírez, S. A. ., & Peña, G. E. . (2011). Análisis de comportamiento caótico en variables de la cadena de suministro. Journal of Economics, Finance and Administrative Science, 16(31), 85–106. https://doi.org/10.46631/jefas.2011.v16n31.05